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SergiioB

SergiioB

@SergiioB · Member since 2026

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Mainly llama.cpp 90 approved runs

Submissions

90

90 approved public runs

Models

20

unique models

Avg output

88.9tok/s

Best 1,140 tok/s

Avg prefill

1,944tok/s

Best 10,371 tok/s

Avg total

249tok/s

Best 2,034 tok/s

Avg TTFT

4,112ms

Best 48.9 ms

Hardware

2

distinct setups

Reactions

2

across all runs

Personal bests

Personal bests20

Fastest approved result for each model.

3B MoE9 runs🔥
Output1,140 tok/s
Prefill8,715 tok/s
TTFT—
Depth—
Intel Arc Pro B70 32GB

vllm · GPTQ-Int4 · 2mo ago

3B MoE10 runs
Output245 tok/s
Prefill4,511 tok/s
TTFT—
Depth0k
Intel Arc Pro B70 32GB

vllm · gptq-int4 · 2w ago

3B MoE1 run
Output245 tok/s
Prefill—
TTFT—
Depth0k
Intel Arc Pro B70 32GB

vllm · gptq-int4 · 2w ago

27B19 runs
Output224 tok/s
Prefill4.8 tok/s
TTFT15,419 ms
Depth—
Intel Arc Pro B70 32GB

vllm · GPTQ-Int4 · 2mo ago

35B MoE7 runs
Output164 tok/s
Prefill383 tok/s
TTFT—
Depth—
Intel Arc Pro B70 32GB

llama.cpp · Q5_K_M · 3mo ago

35B MoE1 run
Output146 tok/s
Prefill—
TTFT—
Depth—
Intel Arc Pro B70 32GB

llama.cpp · Q5_K_M · 3mo ago

27B6 runs
Output113 tok/s
Prefill1,696 tok/s
TTFT—
Depth—
Intel Arc Pro B70 32GB

vllm · GPTQ-Int4+draft-INT4-RTN · 2mo ago

3B MoE3 runs
Output108 tok/s
Prefill9,073 tok/s
TTFT320 ms
Depth—
Intel Arc Pro B70 32GB

vllm · GPTQ-Int4 · 1mo ago

3B MoE1 run
Output87.4 tok/s
Prefill766 tok/s
TTFT—
Depth—
Intel Arc Pro B70 32GB

llama.cpp · Q4_0 · 2mo ago

35B MoE2 runs
Output73.2 tok/s
Prefill416 tok/s
TTFT76.9 ms
Depth—
Intel Arc Pro B70 32GB

llama.cpp · Q4_K_M · 3mo ago

27B7 runs
Output69.3 tok/s
Prefill1,755 tok/s
TTFT—
Depth—
Intel Arc Pro B70 32GB

vllm · GPTQ-Int4 · 2mo ago

3B MoE2 runs
Output62.8 tok/s
Prefill1,682 tok/s
TTFT—
Depth—
Intel Arc Pro B70 32GB

llama.cpp · Q4_K_XL · 3mo ago

9B2 runs
Output50.3 tok/s
Prefill554 tok/s
TTFT57.8 ms
Depth—
Intel Arc Pro B70 32GB

llama.cpp · Q6_K · 3mo ago

180B MoE3 runs
Output33.3 tok/s
Prefill173 tok/s
TTFT—
Depth0k
Intel Arc Pro B70 32GB ×2

llama.cpp · Q4_K_M (AD-4.27bpw M64 dynamic) · 1mo ago

27B2 runs
Output31.1 tok/s
Prefill390 tok/s
TTFT190 ms
Depth—
Intel Arc Pro B70 32GB ×2

vllm · FP8 · 1mo ago

30B3 runs
Output29.2 tok/s
Prefill1,301 tok/s
TTFT—
Depth—
Intel Arc Pro B70 32GB

llama.cpp · Q4_K_XL · 2mo ago

27B3 runs
Output27.9 tok/s
Prefill936 tok/s
TTFT—
Depth—
Intel Arc Pro B70 32GB

llama.cpp · Q6_K · 2mo ago

31B6 runs
Output26.6 tok/s
Prefill385 tok/s
TTFT—
Depth0k
Intel Arc Pro B70 32GB

llama.cpp · Q4_K_M · 2mo ago

27B1 run
Output25.1 tok/s
Prefill613 tok/s
TTFT—
Depth—
Intel Arc Pro B70 32GB

llama.cpp · Q5_K_M · 3mo ago

180B2 runs
Output23.4 tok/s
Prefill184 tok/s
TTFT—
Depth—
Intel Arc Pro B70 32GB ×2

llama.cpp · IQ3_S · 1mo ago

Hardware breakdown

Hardware breakdown2

Distinct rigs used across approved submissions.

Intel Arc Pro B70 32GB

83 runs · best 1,140 tok/s

Intel Arc Pro B70 32GB ×2

7 runs · best 33.3 tok/s

Engines used

Engines used2

Runtime mix and top quantizations.

llama.cpp48Q4_K_M (AD-4.27bpw M64 dynamic) · IQ3_S · Q4_K_M
vllm42gptq-int4 · exl3 · GPTQ-Int4
All runs

All runs90

Full approved speed test history · page 1 of 4.

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · gptq-int4

TTFT

—

Context

2k · 2w ago

Show all run details

Model

nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16

Display name

NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16

Base model

—

Revision

main

Family

—

Parameters

30B

Active params

3B

MoE

yes

Output

245 tok/s

Prefill

4,511 tok/s

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

512

Output tokens

256

Prefill tokens

0

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

—

RAM

—

OS

—

Power

200W

Engine

vllm

Engine version

0.26.1

Quantization

gptq-int4

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

bf16

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

—

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# No command snippet available

Extra flags

—

Notes

MoE vs Dense matched single-card comparison. p512/g128 greedy benchmark on Intel Arc Pro B70 at 200W cap. Yields 244.5 tok/s.

Reactions

—

Submitted

Sep 30, 2026, 7:32 PM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · gptq-int4

TTFT

—

Context

2k · 2w ago

Show all run details

Model

useful-quants/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-W4A16

Display name

NVIDIA-Nemotron-3.5-Lightning-30B-A3B-W4A16

Base model

NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16

Revision

main

Family

—

Parameters

30B

Active params

3B

MoE

yes

Output

245 tok/s

Prefill

—

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

512

Output tokens

128

Prefill tokens

0

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

—

RAM

—

OS

—

Power

200W

Engine

vllm

Engine version

0.26.1

Quantization

gptq-int4

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

bf16

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

—

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# No command snippet available

Extra flags

—

Notes

MoE vs Dense matched single-card comparison. p512/g128 greedy benchmark on Intel Arc Pro B70 at 200W cap. Yields 244.5 tok/s.

Reactions

—

Submitted

Sep 30, 2026, 6:52 PM

Last edited

—

Qwen3.8-27B

27B · Qwen

95.1

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · exl3

TTFT

—

Context

2k · 2w ago

Show all run details

Model

Qwen/Qwen3.8-27B

Display name

Qwen3.8-27B

Base model

—

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

95.1 tok/s

Prefill

—

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

512

Output tokens

128

Prefill tokens

0

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

—

RAM

—

OS

—

Power

200W

Engine

vllm

Engine version

0.26.1

Quantization

exl3

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

—

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# No command snippet available

Extra flags

—

Notes

MoE vs Dense matched single-card comparison. Baseline dense benchmark on Intel Arc Pro B70 at 200W cap. Yields 95.1 tok/s.

Reactions

—

Submitted

Sep 30, 2026, 6:51 PM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · GPTQ-Int4

TTFT

383 ms

Context

16k · 3w ago

Show all run details

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

52.6 tok/s

Prefill

1,347 tok/s

Total

—

TTFT

383 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

516

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (516 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window; 10/10 requests finished_reason=length at exactly 128 tokens

Notes

BASELINE ARM of a matched_with_tokenizer_delta A/B at the short-prompt cell: GPTQ-INT4 g128 sym target + BF16 MTP4 drafter, drafter NOT quantized. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 516 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 383.2 ms. tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.5435 from measured-window counters (804 draft / 437 accepted). POWER: 230 W CONFIGURED CAP; measured avg draw 224.53 W (xe hwmon energy1_input 3277950683 uJ over 14.599 s, bracketing the measured window only); 5.12 J/token over that window INCLUDING prefill; tokens/J 0.1952 (vs 0.2566 patched = +31.4% for the patched arm). RESULT 52.61 vs 73.43 tok/s for the patched arm in this same cell = 1.40x (+39.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 1 tok of 516 = 0.19%); single variable = the two draft-INT4 env gates. Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal emitted class; every emitted token target-verified. ENABLER for the patched effect: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM issue #54785 (2026-09-01) reports capture + MTP num_speculative_tokens=4 can give non-deterministic wrong logits at temperature=0 (k<=3 clean); both arms ran capture-on. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p512-n5-...-20260922T214938Z/.

Reactions

—

Submitted

Sep 22, 2026, 10:58 PM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · GPTQ-Int4

TTFT

352 ms

Context

16k · 3w ago

Show all run details

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

73.4 tok/s

Prefill

1,469 tok/s

Total

—

TTFT

352 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

517

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True -e B70_DRAFT_LMHEAD_INT4=1 -e B70_DRAFT_MTP_INT4=1 --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (517 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window; 10/10 requests finished_reason=length at exactly 128 tokens

Notes

THE IMPROVEMENT at the short-prompt cell: draft-side INT4. Only the MTP drafter's weights are quantized (its 2.54 GB F16 LM head + the MTP body's 5 linears -> W4A16 g128 sym); the 27B target and its verification logits path are untouched. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 517 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 352.0 ms (baseline 383.2 ms - TTFT also improves in this cell). tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.5581 from measured-window counters (792 draft / 442 accepted); run-variable across runs, this cell's patched medians 73.43 (n=5) and 77.14 (n=3 screen), samples 73.4-88.7 (band, not a point). POWER: 230 W CONFIGURED CAP; measured avg draw 228.60 W (xe hwmon energy1_input 2493763306 uJ over 10.909 s, bracketing the measured window only); 3.90 J/token over that window INCLUDING prefill; tokens/J 0.2566 vs 0.1952 baseline = +31.4%. RESULT 73.43 vs 52.61 tok/s = 1.40x (+39.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 1 tok of 517 = 0.19%); single variable = the two draft-INT4 env gates. Same-host re-runs +48.6% (p8192), +37.2/+44.4% (n=5), +46.0% (n=3 screen). Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal class. ENABLER: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM #54785 reports capture+MTP4 can give non-deterministic wrong logits at temp=0 (k<=3 clean); both arms capture-on so the A/B is consistent. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p512-n5-...-20260922T214938Z/.

Reactions

—

Submitted

Sep 22, 2026, 10:57 PM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · GPTQ-Int4

TTFT

4,738 ms

Context

16k · 3w ago

Show all run details

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

48.8 tok/s

Prefill

1,729 tok/s

Total

—

TTFT

4,738 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

8190

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (8190 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window (unique cold prompt with entropy nonce); 10/10 requests finished_reason=length at exactly 128 tokens

Notes

BASELINE ARM of a matched_with_tokenizer_delta A/B: GPTQ-INT4 g128 sym target + BF16 MTP4 drafter, drafter NOT quantized. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 8190 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 4738.1 ms. tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.4873 from measured-window counters (864 draft / 421 accepted); run-variable, 0.4873 this run vs 0.53-0.58 in the earlier baseline run - this run's baseline arm is at the low tail of acceptance and throughput, so the 1.49x here is the HIGH end of the reproduced +37.2/+44.4/+48.6% range. POWER: 230 W CONFIGURED CAP; measured avg draw 228.74 W (xe hwmon energy1_input 10730884522 uJ over 46.914 s, bracketing the measured window only); 16.77 J/token over that window INCLUDING prefill; tokens/J 0.0596 (vs 0.0654 patched = +9.6% for the patched arm). RESULT 48.81 vs 72.55 tok/s for the patched arm in this same cell = 1.49x (+48.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 4 tok of 8190 = 0.05%); single variable = the two draft-INT4 env gates. Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal emitted class; every emitted token target-verified. ENABLER for the patched effect: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM issue #54785 (2026-09-01) reports capture + MTP num_speculative_tokens=4 can give non-deterministic wrong logits at temperature=0 (k<=3 clean); both arms ran capture-on. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p8192-n5-...-20260922T213957Z/.

Reactions

—

Submitted

Sep 22, 2026, 10:56 PM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · GPTQ-Int4

TTFT

4,792 ms

Context

16k · 3w ago

Show all run details

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

72.6 tok/s

Prefill

1,710 tok/s

Total

—

TTFT

4,792 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

8194

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True -e B70_DRAFT_LMHEAD_INT4=1 -e B70_DRAFT_MTP_INT4=1 --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (8194 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window (unique cold prompt with entropy nonce); 10/10 requests finished_reason=length at exactly 128 tokens

Notes

THE IMPROVEMENT: draft-side INT4. Only the MTP drafter's weights are quantized (its 2.54 GB F16 LM head + the MTP body's 5 linears -> W4A16 g128 sym); the 27B target and its verification logits path are untouched. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 8194 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 4791.6 ms. tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.5676 from measured-window counters (784 draft / 445 accepted); run-variable across same-host runs 0.55-0.70 (this 0.5676); patched medians span 72.55-80.32, within-run samples 64.25-91.17 (band, not a point). POWER: 230 W CONFIGURED CAP; measured avg draw 229.50 W (xe hwmon energy1_input 9788913941 uJ over 42.654 s, bracketing the measured window only); 15.30 J/token over that window INCLUDING prefill; tokens/J 0.0654 vs 0.0596 baseline = +9.6%. RESULT 72.55 vs 48.81 tok/s = 1.49x (+48.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 4 tok of 8194 = 0.05%); single variable = the two draft-INT4 env gates. Same-host re-runs +39.6% (p512), +37.2/+44.4% (n=5), +46.0% (n=3 screen); a both-arms-patched control gave 80.61/78.27 tok/s. Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal emitted class. ENABLER: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM #54785 reports capture+MTP4 can give non-deterministic wrong logits at temp=0 (k<=3 clean); both arms capture-on so the A/B is consistent. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p8192-n5-...-20260922T213957Z/.

Reactions

—

Submitted

Sep 22, 2026, 10:55 PM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · GPTQ-Int4

TTFT

383 ms

Context

16k · 3w ago

Show all run details

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

52.6 tok/s

Prefill

1,347 tok/s

Total

—

TTFT

383 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

516

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (516 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window; 10/10 requests finished_reason=length at exactly 128 tokens

Notes

BASELINE ARM of a matched_with_tokenizer_delta A/B at the short-prompt cell: GPTQ-INT4 g128 sym target + BF16 MTP4 drafter, drafter NOT quantized. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 516 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 383.2 ms. tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.5435 from measured-window counters (804 draft / 437 accepted). POWER: 230 W CONFIGURED CAP; measured avg draw 224.53 W (xe hwmon energy1_input 3277950683 uJ over 14.599 s, bracketing the measured window only); 5.12 J/token over that window INCLUDING prefill; tokens/J 0.1952 (vs 0.2566 patched = +31.4% for the patched arm). RESULT 52.61 vs 73.43 tok/s for the patched arm in this same cell = 1.40x (+39.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 1 tok of 516 = 0.19%); single variable = the two draft-INT4 env gates. Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal emitted class; every emitted token target-verified. ENABLER for the patched effect: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM issue #54785 (2026-09-01) reports capture + MTP num_speculative_tokens=4 can give non-deterministic wrong logits at temperature=0 (k<=3 clean); both arms ran capture-on. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p512-n5-...-20260922T214938Z/.

Reactions

—

Submitted

Sep 22, 2026, 10:52 PM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · GPTQ-Int4

TTFT

352 ms

Context

16k · 3w ago

Show all run details

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

73.4 tok/s

Prefill

1,469 tok/s

Total

—

TTFT

352 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

517

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True -e B70_DRAFT_LMHEAD_INT4=1 -e B70_DRAFT_MTP_INT4=1 --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (517 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window; 10/10 requests finished_reason=length at exactly 128 tokens

Notes

THE IMPROVEMENT at the short-prompt cell: draft-side INT4. Only the MTP drafter's weights are quantized (its 2.54 GB F16 LM head + the MTP body's 5 linears -> W4A16 g128 sym); the 27B target and its verification logits path are untouched. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 517 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 352.0 ms, improved vs baseline 383.2 ms (NOT unchanged). tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.5581 from measured-window counters (792 draft / 442 accepted); run-variable 0.55-0.70 across same-host runs; patched medians span 72.55-80.32, within-run samples 64.25-91.17 (band, not a point). POWER: 230 W CONFIGURED CAP; measured avg draw 228.59 W (xe hwmon energy1_input 2493763306 uJ over 10.909 s, bracketing the measured window only); 3.89 J/token over that window INCLUDING prefill; tokens/J 0.2566 vs 0.1952 baseline = +31.4%. RESULT 73.43 vs 52.61 tok/s = 1.40x (+39.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 1 tok of 517 = 0.19%); single variable = the two draft-INT4 env gates. Same-host re-runs +48.6% (p8192), +37.2/+44.4% (n=5), +46.0% (n=3 screen). Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal class. ENABLER: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM #54785 reports capture+MTP4 can give non-deterministic wrong logits at temp=0 (k<=3 clean); both arms capture-on so the A/B is consistent. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p512-n5-...-20260922T214938Z/.

Reactions

—

Submitted

Sep 22, 2026, 10:51 PM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · GPTQ-Int4

TTFT

4,738 ms

Context

16k · 3w ago

Show all run details

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

48.8 tok/s

Prefill

1,729 tok/s

Total

—

TTFT

4,738 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

8190

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (8190 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window (unique cold prompt with entropy nonce); 10/10 requests finished_reason=length at exactly 128 tokens

Notes

BASELINE ARM of a matched_with_tokenizer_delta A/B: GPTQ-INT4 g128 sym target + BF16 MTP4 drafter, drafter NOT quantized. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 8190 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 4738.1 ms. tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.4873 from measured-window counters (864 draft / 421 accepted); run-variable, 0.4873 this run vs 0.53-0.58 in the earlier baseline run - this run's baseline arm is at the low tail of acceptance and throughput, so the 1.49x here is the HIGH end of the reproduced +37.2/+44.4/+48.6% range. POWER: 230 W CONFIGURED CAP; measured avg draw 228.74 W (xe hwmon energy1_input 10730884522 uJ over 46.914 s, bracketing the measured window only); 16.77 J/token over that window INCLUDING prefill; tokens/J 0.0596 (vs 0.0654 patched = +9.6% for the patched arm). RESULT 48.81 vs 72.55 tok/s for the patched arm in this same cell = 1.49x (+48.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 4 tok of 8190 = 0.05%); single variable = the two draft-INT4 env gates. Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal emitted class; every emitted token target-verified. ENABLER for the patched effect: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM issue #54785 (2026-09-01) reports capture + MTP num_speculative_tokens=4 can give non-deterministic wrong logits at temperature=0 (k<=3 clean); both arms ran capture-on. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p8192-n5-...-20260922T213957Z/.

Reactions

—

Submitted

Sep 22, 2026, 10:50 PM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · GPTQ-Int4

TTFT

4,792 ms

Context

16k · 3w ago

Show all run details

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

72.6 tok/s

Prefill

1,710 tok/s

Total

—

TTFT

4,792 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

8194

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True -e B70_DRAFT_LMHEAD_INT4=1 -e B70_DRAFT_MTP_INT4=1 --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (8194 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window (unique cold prompt with entropy nonce); 10/10 requests finished_reason=length at exactly 128 tokens

Notes

THE IMPROVEMENT: draft-side INT4. Only the MTP drafter's weights are quantized (its 2.54 GB F16 LM head + the MTP body's 5 linears -> W4A16 g128 sym); the 27B target and its verification logits path are untouched. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 8194 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 4791.6 ms. tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.5676 from measured-window counters (784 draft / 445 accepted); run-variable across same-host runs 0.55-0.70 (this 0.5676); patched medians span 72.55-80.32, within-run samples 64.25-91.17 (band, not a point). POWER: 230 W CONFIGURED CAP; measured avg draw 229.49 W (xe hwmon energy1_input 9788913941 uJ over 42.654 s, bracketing the measured window only); 15.29 J/token over that window INCLUDING prefill; tokens/J 0.0654 vs 0.0596 baseline = +9.6%. RESULT 72.55 vs 48.81 tok/s = 1.49x (+48.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 4 tok of 8194 = 0.05%); single variable = the two draft-INT4 env gates. Same-host re-runs +39.6% (p512), +37.2/+44.4% (n=5), +46.0% (n=3 screen); a both-arms-patched control gave 80.61/78.27 tok/s. Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal emitted class. ENABLER: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM #54785 reports capture+MTP4 can give non-deterministic wrong logits at temp=0 (k<=3 clean); both arms capture-on so the A/B is consistent. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p8192-n5-...-20260922T213957Z/.

Reactions

—

Submitted

Sep 22, 2026, 10:48 PM

Last edited

—

Qwen3.8-Flash-Next-GGUF

180B MoE · Qwen

33.3

tok/s

Hardware

Intel Arc Pro B70 32GB ×2

Engine

llama.cpp · Q4_K_M (AD-4.27bpw M64 dynamic)

TTFT

—

Context

8k · 1mo ago

Show all run details

Model

AtomicChat/Qwen3.8-Flash-Next-GGUF

Display name

Qwen3.8-Flash-Next-GGUF

Base model

Qwen3.8-Flash-Next

Revision

main

Family

Qwen

Parameters

180B

Active params

—

MoE

yes

Output

33.3 tok/s

Prefill

173 tok/s

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

0

Output tokens

0

Prefill tokens

0

Context length

8192

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB ×2

GPU slots

—

GPU count

2

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (6 decode / 14 batch threads)

RAM

60GB

OS

Linux

Power

195W

Engine

llama.cpp

Engine version

SYCL 0.3.0-dev @ 52d4268 + qwen4exp MTP port + local multi-token verify kernel

Quantization

Q4_K_M (AD-4.27bpw M64 dynamic)

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

99

Split mode

layer

KV cache dtype

q8_0/q4_1

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

yes

Chunked prefill

—

Prefill chunk

512

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

1

Concurrency

—

Spec decoding

yes

Spec method

MTP

Spec model

Qwen3.8-Flash-Next-MTP-Q4_K_M.gguf

Spec draft model

—

Spec tokens

3

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

—

Temperature

6

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

LLAMA_ATTN_ROT_DISABLE=1 llama-server -m Qwen3.8-Flash-Next-AD-4.27bpw-Q4_K_M-M64.gguf -md Qwen3.8-Flash-Next-MTP-Q4_K_M.gguf -ngld 999 --spec-type draft-mtp --spec-draft-n-max 3 --spec-draft-p-min 0.75 --spec-draft-backend-sampling --spec-draft-device SYCL1 --device SYCL0,SYCL1 --tensor-split 1,1 --split-mode layer -ngl 99 -ot per_layer_token_embd=CPU -fa on -t 6 -tb 14 -np 1 -c 8192 -b 512 --ubatch-size 512 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Extra flags

--ngld 999 --spec-draft-p-min 0.75 --spec-draft-backend-sampling --spec-draft-device SYCL1 --tensor-split 1,1 --ot per_layer_token_embd=CPU --tb 14 --b 512 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Notes

Qwen3.8-Flash-Next 125B-A6B MoE + 51B n-gram PLE table (35.76 GiB Q5_1) mmap host, page-cache pre-warmed. Quant: AtomicChat AD-4.27bpw Q4_K_M M64 + dzannotti MTP draft head Q4_K_M. Self-measured engine-native C1, single client, 195 W cap, sampling t=1.0/top_p 0.95/top_k 20, ignore_eos, zero cache reuse, exact token counts. Local multi-token MoE kernel (fused MUL_MAT_ID for M=2..8, both gate_up and grouped down forms) wired into llama.cpp SYCL 52d4268 + qwen4exp MTP port; round cost 118->~85 ms vs unpatched. Long context: c16 P~8.5K prose 30.85 median decode / 412 cold input (n=5); c131072 near-boundary P~120K completed n=5 (first on this host): 18.38 median decode / 222.9 cold input, capacity-observation tier. Acceptance 79-83% on matched natural prompts (code > prose); quality battery 42/42, divergence inside spec-OFF envelope. PROVISIONAL self-report, not independently reproduced.

Reactions

—

Submitted

Sep 11, 2026, 1:05 PM

Last edited

—

Qwen3.8-Flash-Next-GGUF

180B MoE · Qwen

23.0

tok/s

Hardware

Intel Arc Pro B70 32GB ×2

Engine

llama.cpp · Q4_K_M (AD-4.27bpw M64 dynamic)

TTFT

—

Context

16k · 1mo ago

Show all run details

Model

AtomicChat/Qwen3.8-Flash-Next-GGUF

Display name

Qwen3.8-Flash-Next-GGUF

Base model

Qwen3.8-Flash-Next

Revision

main

Family

Qwen

Parameters

180B

Active params

—

MoE

yes

Output

23.0 tok/s

Prefill

586 tok/s

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

0

Output tokens

0

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB ×2

GPU slots

—

GPU count

2

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (6 decode / 14 batch threads)

RAM

60GB

OS

Linux

Power

195W

Engine

llama.cpp

Engine version

SYCL 0.3.0-dev @ 52d4268, GGML_SYCL_F16=ON build

Quantization

Q4_K_M (AD-4.27bpw M64 dynamic)

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

99

Split mode

layer

KV cache dtype

q8_0/q4_1

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

yes

Chunked prefill

—

Prefill chunk

3072

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

1

Concurrency

—

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

6

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

llama-server -m Qwen3.8-Flash-Next-AD-4.27bpw-Q4_K_M-M64.gguf --device SYCL0,SYCL1 --tensor-split 1,1 --split-mode layer -ngl 99 -ot per_layer_token_embd=CPU -fa on -t 6 -tb 14 -np 1 -c 16384 -b 3072 --ubatch-size 3072 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Extra flags

--tensor-split 1,1 --ot per_layer_token_embd=CPU --tb 14 --b 3072 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Notes

Prefill record (separate from decode record by design: different binary/spec). Quant: AtomicChat AD-4.27bpw Q4_K_M M64 GGUF. F16-accumulation binary is worth ~+38% vs FP32 at b3072. Self-measured engine-native C1, single client, n=3 median, P9096(actual)/G128/C1 COLD INPUT rate (llama.cpp HTTP full uncached prompt, not llama-bench pp), zero prompt-cache reuse verified per sample, stdev 0.2. Decode in same cell 22.96 tok/s (no-spec F16). PLE table mmap host. PROVISIONAL self-report, not independently reproduced.

Reactions

—

Submitted

Sep 11, 2026, 6:15 AM

Last edited

—

Qwen3.8-Flash-Next-GGUF

180B MoE · Qwen

27.7

tok/s

Hardware

Intel Arc Pro B70 32GB ×2

Engine

llama.cpp · Q4_K_M (AD-4.27bpw M64 dynamic)

TTFT

—

Context

8k · 1mo ago

Show all run details

Model

AtomicChat/Qwen3.8-Flash-Next-GGUF

Display name

Qwen3.8-Flash-Next-GGUF

Base model

Qwen3.8-Flash-Next

Revision

main

Family

Qwen

Parameters

180B

Active params

—

MoE

yes

Output

27.7 tok/s

Prefill

173 tok/s

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

0

Output tokens

0

Prefill tokens

0

Context length

8192

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB ×2

GPU slots

—

GPU count

2

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (6 decode / 14 batch threads)

RAM

60GB

OS

Linux

Power

195W

Engine

llama.cpp

Engine version

SYCL 0.3.0-dev @ 52d4268 + qwen4exp MTP port + local multi-token verify kernel

Quantization

Q4_K_M (AD-4.27bpw M64 dynamic)

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

99

Split mode

layer

KV cache dtype

q8_0/q4_1

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

yes

Chunked prefill

—

Prefill chunk

512

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

1

Concurrency

—

Spec decoding

yes

Spec method

MTP

Spec model

Qwen3.8-Flash-Next-MTP-Q4_K_M.gguf

Spec draft model

—

Spec tokens

3

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

—

Temperature

6

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

LLAMA_ATTN_ROT_DISABLE=1 llama-server -m Qwen3.8-Flash-Next-AD-4.27bpw-Q4_K_M-M64.gguf -md Qwen3.8-Flash-Next-MTP-Q4_K_M.gguf -ngld 999 --spec-type draft-mtp --spec-draft-n-max 3 --spec-draft-p-min 0.75 --spec-draft-backend-sampling --spec-draft-device SYCL1 --device SYCL0,SYCL1 --tensor-split 1,1 --split-mode layer -ngl 99 -ot per_layer_token_embd=CPU -fa on -t 6 -tb 14 -np 1 -c 8192 -b 512 --ubatch-size 512 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Extra flags

--ngld 999 --spec-draft-p-min 0.75 --spec-draft-backend-sampling --spec-draft-device SYCL1 --tensor-split 1,1 --ot per_layer_token_embd=CPU --tb 14 --b 512 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Notes

Qwen3.8-Flash-Next 125B-A6B MoE (48L: 36 GDN + 12 QSA, 512 experts top-10) + 51B n-gram PLE table (35.76 GiB Q5_1) mmap host, page-cache pre-warmed. Quant: AtomicChat AD-4.27bpw Q4_K_M M64 GGUF + dzannotti MTP draft head Q4_K_M (-md). Self-measured engine-native C1 timing (not client-side), single client, n=5 fresh-server median, P512(actual)/G128/C1, range 22.63-28.88 (unwarmed twin 26.33; warm-server n=3 29.90). MTP acceptance 87.7% (13,156/14,996, 7,158 rounds) on natural prose+code; quality battery 42/42 code tests, divergence inside spec-OFF envelope. MTP needs local qwen4exp port (not upstream at 52d4268); LLAMA_ATTN_ROT_DISABLE=1 mandatory with quantized KV. PROVISIONAL self-report, not independently reproduced. Prefill 512-cell cold input 173 tok/s; long-prompt prefill is a separate record.

Reactions

—

Submitted

Sep 11, 2026, 6:15 AM

Last edited

—

Qwen3.8-Flash-Next

180B · Qwen

20.3

tok/s

Hardware

Intel Arc Pro B70 32GB ×2

Engine

llama.cpp · IQ3_S

TTFT

—

Context

16k · 1mo ago

Show all run details

Model

Qwen/Qwen3.8-Flash-Next

Display name

Qwen3.8-Flash-Next

Base model

—

Revision

main

Family

Qwen

Parameters

180B

Active params

—

MoE

no

Output

20.3 tok/s

Prefill

594 tok/s

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

0

Output tokens

0

Prefill tokens

—

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB ×2

GPU slots

—

GPU count

2

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

—

RAM

—

OS

Linux

Power

—

Engine

llama.cpp

Engine version

0.3.0-dev b492 9723942 SYCL F16=ON

Quantization

IQ3_S

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

99

Split mode

layer

KV cache dtype

q8_0/q4_1

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

yes

Chunked prefill

—

Prefill chunk

3072

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

1

Concurrency

—

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

6

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

llama-server -m Qwen3.8-Flash-Next-AD-4.27bpw-Q4_K_M-M64-00001-of-00033.gguf --device SYCL0,SYCL1 --tensor-split 1,1 --split-mode layer -ngl 99 -ot per_layer_token_embd=CPU -c 16384 -fa on -t 6 -tb 14 -np 1 -b 3072 --ubatch-size 3072 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Extra flags

--tensor-split 1,1 --ot per_layer_token_embd=CPU --tb 14 --b 3072 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Notes

C1 only (-np 1, one client). c16 means context 16384, not concurrency 16. Prefill = llama.cpp engine timings.prompt_per_second median n=5 at actual p9096/g128, fused IQ3_S/IQ4_NL MMVQ, GGML_SYCL_F16=ON, -b/-ub 3072, cache_n=0. Decode on this same F16 server is 20.34, not the fused-FP32 23.38 cell. Artifact AtomicChat Qwen3.8-Flash-Next-AD-4.27bpw-Q4_K_M-M64 rev 142262902a46f7daed19c79d0771534c8106ad59. Mixed: gate/up IQ3_S, down IQ4_NL, PLE Q5_1 CPU mmap (platform quantization field is IQ3_S). KV q8_0/q4_1, FA on, layer split 1,1, 195 W configured cap. Loaded-idle GPU1 pkg ~62 C. E2 self-report. Independent reproduction pending. Patches: patches/llamacpp-sycl/flashnext-arch-overlay.patch then sycl-fused-mmvq-and-gpu-group.patch.

Reactions

—

Submitted

Sep 1, 2026, 9:24 AM

Last edited

—

Qwen3.8-Flash-Next

180B · Qwen

23.4

tok/s

Hardware

Intel Arc Pro B70 32GB ×2

Engine

llama.cpp · IQ3_S

TTFT

—

Context

8k · 1mo ago

Show all run details

Model

Qwen/Qwen3.8-Flash-Next

Display name

Qwen3.8-Flash-Next

Base model

—

Revision

main

Family

Qwen

Parameters

180B

Active params

—

MoE

no

Output

23.4 tok/s

Prefill

184 tok/s

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

0

Output tokens

0

Prefill tokens

—

Context length

8192

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB ×2

GPU slots

—

GPU count

2

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

—

RAM

—

OS

Linux

Power

—

Engine

llama.cpp

Engine version

0.3.0-dev b492 9723942 SYCL F16=OFF

Quantization

IQ3_S

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

99

Split mode

layer

KV cache dtype

q8_0/q4_1

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

yes

Chunked prefill

—

Prefill chunk

512

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

1

Concurrency

—

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

6

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

llama-server -m Qwen3.8-Flash-Next-AD-4.27bpw-Q4_K_M-M64-00001-of-00033.gguf --device SYCL0,SYCL1 --tensor-split 1,1 --split-mode layer -ngl 99 -ot per_layer_token_embd=CPU -c 8192 -fa on -t 6 -tb 14 -np 1 -b 512 --ubatch-size 512 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Extra flags

--tensor-split 1,1 --ot per_layer_token_embd=CPU --tb 14 --b 512 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Notes

C1 only (-np 1, one client). c8 means context 8192, not concurrency 8. Decode = llama.cpp engine timings.predicted_per_second median n=5 at p512/g128, fused IQ3_S/IQ4_NL MMVQ, GGML_SYCL_F16=OFF. Cold input = timings.prompt_per_second with cache_n=0 (183.98). Do not mix this decode number with the fused-F16 594.49 prefill cell (separate binary). Artifact AtomicChat Qwen3.8-Flash-Next-AD-4.27bpw-Q4_K_M-M64 rev 142262902a46f7daed19c79d0771534c8106ad59. Mixed: gate/up IQ3_S, down IQ4_NL, PLE Q5_1 CPU mmap (platform quantization field is IQ3_S). KV q8_0/q4_1, FA on, layer split 1,1, 195 W configured cap. Loaded-idle GPU1 pkg ~62 C, not ordinary <=55 C. E2 self-report. Independent reproduction pending. Patches: patches/llamacpp-sycl/flashnext-arch-overlay.patch then sycl-fused-mmvq-and-gpu-group.patch.

Reactions

—

Submitted

Sep 1, 2026, 9:24 AM

Last edited

—

Qwen3.8-27B-FP8

27B · Qwen

31.1

tok/s

Hardware

Intel Arc Pro B70 32GB ×2

Engine

vllm · FP8

TTFT

190 ms

Context

2k · 1mo ago

Show all run details

Model

Qwen/Qwen3.8-27B-FP8

Display name

Qwen3.8-27B-FP8

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

31.1 tok/s

Prefill

390 tok/s

Total

39.4 tok/s

TTFT

190 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

74

Output tokens

256

Prefill tokens

—

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB ×2

GPU slots

—

GPU count

2

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

FP8

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

—

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8920 servedModel: qw38-fp8

Extra flags

—

Notes

—

Reactions

—

Submitted

Aug 30, 2026, 6:06 PM

Last edited

—

Qwen3.8-27B-FP8

27B · Qwen

28.6

tok/s

Hardware

Intel Arc Pro B70 32GB ×2

Engine

vllm · FP8

TTFT

205 ms

Context

2k · 1mo ago

Show all run details

Model

Qwen/Qwen3.8-27B-FP8

Display name

Qwen3.8-27B-FP8

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

28.6 tok/s

Prefill

361 tok/s

Total

36.2 tok/s

TTFT

205 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

74

Output tokens

256

Prefill tokens

—

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB ×2

GPU slots

—

GPU count

2

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

FP8

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

—

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8920 servedModel: qw38-fp8

Extra flags

—

Notes

—

Reactions

—

Submitted

Aug 30, 2026, 4:04 PM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · GPTQ-Int4

TTFT

320 ms

Context

2k · 1mo ago

Show all run details

Model

SergiioB/Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

Display name

Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

Base model

Ornith-1.5-35B-A3B

Revision

main

Family

Qwen

Parameters

35B

Active params

3B

MoE

yes

Output

108 tok/s

Prefill

9,073 tok/s

Total

2,034 tok/s

TTFT

320 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

2906

Output tokens

128

Prefill tokens

—

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

GPTQ-Int4

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

—

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8000 servedModel: ornith15

Extra flags

—

Notes

—

Reactions

—

Submitted

Aug 21, 2026, 10:36 AM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · GPTQ-Int4

TTFT

297 ms

Context

2k · 1mo ago

Show all run details

Model

SergiioB/Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

Display name

Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

Base model

Ornith-1.5-35B-A3B

Revision

main

Family

Qwen

Parameters

35B

Active params

3B

MoE

yes

Output

69.9 tok/s

Prefill

9,780 tok/s

Total

1,435 tok/s

TTFT

297 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

2906

Output tokens

128

Prefill tokens

—

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

GPTQ-Int4

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

—

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8000 servedModel: ornith15

Extra flags

—

Notes

—

Reactions

—

Submitted

Aug 21, 2026, 10:18 AM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · GPTQ-Int4

TTFT

48.9 ms

Context

2k · 1mo ago

Show all run details

Model

SergiioB/Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

Display name

Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

Base model

Ornith-1.5-35B-A3B

Revision

main

Family

Qwen

Parameters

35B

Active params

3B

MoE

yes

Output

94.1 tok/s

Prefill

655 tok/s

Total

104 tok/s

TTFT

48.9 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

32

Output tokens

256

Prefill tokens

—

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

150W

Engine

vllm

Engine version

—

Quantization

GPTQ-Int4

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

—

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8000 servedModel: ornith15

Extra flags

—

Notes

—

Reactions

—

Submitted

Aug 21, 2026, 10:14 AM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · GPTQ-Int4

TTFT

24,360 ms

Context

131k · 2mo ago

Show all run details

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

108 tok/s

Prefill

1,694 tok/s

Total

70.8 tok/s

TTFT

24,360 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

74

Output tokens

256

Prefill tokens

—

Context length

131072

Batch size

5

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

GPTQ-Int4

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

yes

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

5

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8000 servedModel: qwen38

Extra flags

—

Notes

Single Intel Arc Pro B70 32GB. Stack: vLLM XPU nightly f01e24f6, MTP4, GDN mixed-split v5, draft-INT4 S+M1, prefix caching ON. Realistic 5-user coding serving at the Qwen3.8-27B model-card RECOMMENDED non-thinking sampling (temperature=0.7, top_p=0.80, top_k=20, presence_penalty=1.5). 5 concurrent multi-turn coding sessions, ~8K session prompts, 512-token generations, 45/45 OK, real completions in history. tokSOut = sum of per-stream rates (5 x 21.6 median per-user tok/s). Per-turn Sigma: t1 134.4 / t2 106.3 / t3 100.5. TTFT 21-26s per turn (prefix cache lands 0-38% of shared tokens at C5 on this build). MTP acceptance 34-41% under concurrency. Greedy sibling: 127.4 Sigma.

Reactions

—

Submitted

Aug 19, 2026, 1:39 PM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · GPTQ-Int4

TTFT

337 ms

Context

131k · 2mo ago

Show all run details

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

103 tok/s

Prefill

1,694 tok/s

Total

70.8 tok/s

TTFT

337 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

74

Output tokens

256

Prefill tokens

—

Context length

131072

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

GPTQ-Int4

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

yes

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8000 servedModel: qwen38

Extra flags

—

Notes

Single Intel Arc Pro B70 32GB. Stack: vLLM XPU nightly f01e24f6, MTP4, GDN mixed-split v5, draft-INT4 S+M1, prefix caching ON. Qwen3.8-27B model-card RECOMMENDED non-thinking sampling: temperature=0.7, top_p=0.80, top_k=20, presence_penalty=1.5. C1 client post-first, n=5 median 102.61 (95.7-106.7), calibrated real-world Pi prompts, MTP acceptance 91.8%. Greedy sibling on the same stack: 106.7 (93% acceptance) - recommended sampling costs ~4% here. Cold input 1694 tok/s p8192/g1.

Reactions

—

Submitted

Aug 19, 2026, 1:39 PM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · GPTQ-Int4

TTFT

22,850 ms

Context

131k · 2mo ago

Show all run details

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

127 tok/s

Prefill

1,694 tok/s

Total

70.8 tok/s

TTFT

22,850 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

74

Output tokens

256

Prefill tokens

—

Context length

131072

Batch size

5

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

GPTQ-Int4

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

yes

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8000 servedModel: qwen38

Extra flags

—

Notes

Self-reported. Single Intel Arc Pro B70 32GB. Realistic 5-user coding serving, v2 with REAL completions kept in session history (supersedes the stubbed same-day 138.3 record). Stack: vLLM XPU nightly f01e24f6, MTP4, GDN mixed-split v5, draft-INT4 S+M1, prefix caching ON. 5 concurrent sessions, ~8K start, 3 turns, g512, 60/60 OK. tokSOut = sum of per-stream generation rates (5 x 25.5 median per-user tok/s, all turns). Per-turn: t1 165.5, t2 127.9, t3 114.2 aggregate. TTFT 22.6-25.0s every turn: prefix cache lands 0-38% of shared tokens at C5 on this build (vs 91% at C1), so ~45-53K session tokens re-prefill per turn. MTP acceptance 43-56% under concurrency. Short-prompt C5 (203.8) is a separate record; C1 is 106.7.

Reactions

—

Submitted

Aug 19, 2026, 12:59 PM

Last edited

—

Hardware

Intel Arc Pro B70 32GB

Engine

vllm · GPTQ-Int4

TTFT

335 ms

Context

131k · 2mo ago

Show all run details

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

107 tok/s

Prefill

1,694 tok/s

Total

70.8 tok/s

TTFT

335 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

74

Output tokens

256

Prefill tokens

—

Context length

131072

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

GPTQ-Int4

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

yes

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8000 servedModel: qwen38

Extra flags

—

Notes

Self-reported. Single Intel Arc Pro B70 32GB. Current full stack: vLLM XPU nightly f01e24f6, MTP4, GDN mixed-split v5, draft-INT4 S+M1, prefix caching ON (zero hits, unique prompts). C1 client post-first, n=5 median 106.7 (103.2-111.3), calibrated real-world Pi prompt set; MTP acceptance 89-96%; cold input 1694 tok/s at p8192/g1. Supersedes same-day 100.2 (same config, run-to-run variance). Cache-off sibling record: 112.65. Degenerate INDEX filler measures ~71 (44% acceptance) - prompt family matters.

Reactions

—

Submitted

Aug 19, 2026, 12:59 PM

Last edited

—

ModelHardwareEnginetok/s outprefilltok/s totalTTFTDepthShare
NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16

3B MoE

Intel Arc Pro B70 32GB
vllmgptq-int42454,511——0k
Show all details for NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16

Model

nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16

Display name

NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16

Base model

—

Revision

main

Family

—

Parameters

30B

Active params

3B

MoE

yes

Output

245 tok/s

Prefill

4,511 tok/s

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

512

Output tokens

256

Prefill tokens

0

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

—

RAM

—

OS

—

Power

200W

Engine

vllm

Engine version

0.26.1

Quantization

gptq-int4

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

bf16

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

—

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# No command snippet available

Extra flags

—

Notes

MoE vs Dense matched single-card comparison. p512/g128 greedy benchmark on Intel Arc Pro B70 at 200W cap. Yields 244.5 tok/s.

Reactions

—

Submitted

Sep 30, 2026, 7:32 PM

Last edited

—

NVIDIA-Nemotron-3.5-Lightning-30B-A3B-W4A16

3B MoE

Intel Arc Pro B70 32GB
vllmgptq-int4245———0k
Show all details for NVIDIA-Nemotron-3.5-Lightning-30B-A3B-W4A16

Model

useful-quants/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-W4A16

Display name

NVIDIA-Nemotron-3.5-Lightning-30B-A3B-W4A16

Base model

NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16

Revision

main

Family

—

Parameters

30B

Active params

3B

MoE

yes

Output

245 tok/s

Prefill

—

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

512

Output tokens

128

Prefill tokens

0

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

—

RAM

—

OS

—

Power

200W

Engine

vllm

Engine version

0.26.1

Quantization

gptq-int4

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

bf16

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

—

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# No command snippet available

Extra flags

—

Notes

MoE vs Dense matched single-card comparison. p512/g128 greedy benchmark on Intel Arc Pro B70 at 200W cap. Yields 244.5 tok/s.

Reactions

—

Submitted

Sep 30, 2026, 6:52 PM

Last edited

—

Qwen3.8-27B

27B · Qwen

Intel Arc Pro B70 32GB
vllmexl395.1———0k
Show all details for Qwen3.8-27B

Model

Qwen/Qwen3.8-27B

Display name

Qwen3.8-27B

Base model

—

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

95.1 tok/s

Prefill

—

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

512

Output tokens

128

Prefill tokens

0

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

—

RAM

—

OS

—

Power

200W

Engine

vllm

Engine version

0.26.1

Quantization

exl3

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

—

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# No command snippet available

Extra flags

—

Notes

MoE vs Dense matched single-card comparison. Baseline dense benchmark on Intel Arc Pro B70 at 200W cap. Yields 95.1 tok/s.

Reactions

—

Submitted

Sep 30, 2026, 6:51 PM

Last edited

—

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

27B · Qwen

Intel Arc Pro B70 32GB
vllmGPTQ-Int452.61,347—383 ms0k
Show all details for Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

52.6 tok/s

Prefill

1,347 tok/s

Total

—

TTFT

383 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

516

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (516 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window; 10/10 requests finished_reason=length at exactly 128 tokens

Notes

BASELINE ARM of a matched_with_tokenizer_delta A/B at the short-prompt cell: GPTQ-INT4 g128 sym target + BF16 MTP4 drafter, drafter NOT quantized. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 516 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 383.2 ms. tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.5435 from measured-window counters (804 draft / 437 accepted). POWER: 230 W CONFIGURED CAP; measured avg draw 224.53 W (xe hwmon energy1_input 3277950683 uJ over 14.599 s, bracketing the measured window only); 5.12 J/token over that window INCLUDING prefill; tokens/J 0.1952 (vs 0.2566 patched = +31.4% for the patched arm). RESULT 52.61 vs 73.43 tok/s for the patched arm in this same cell = 1.40x (+39.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 1 tok of 516 = 0.19%); single variable = the two draft-INT4 env gates. Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal emitted class; every emitted token target-verified. ENABLER for the patched effect: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM issue #54785 (2026-09-01) reports capture + MTP num_speculative_tokens=4 can give non-deterministic wrong logits at temperature=0 (k<=3 clean); both arms ran capture-on. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p512-n5-...-20260922T214938Z/.

Reactions

—

Submitted

Sep 22, 2026, 10:58 PM

Last edited

—

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

27B · Qwen

Intel Arc Pro B70 32GB
vllmGPTQ-Int473.41,469—352 ms0k
Show all details for Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

73.4 tok/s

Prefill

1,469 tok/s

Total

—

TTFT

352 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

517

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True -e B70_DRAFT_LMHEAD_INT4=1 -e B70_DRAFT_MTP_INT4=1 --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (517 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window; 10/10 requests finished_reason=length at exactly 128 tokens

Notes

THE IMPROVEMENT at the short-prompt cell: draft-side INT4. Only the MTP drafter's weights are quantized (its 2.54 GB F16 LM head + the MTP body's 5 linears -> W4A16 g128 sym); the 27B target and its verification logits path are untouched. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 517 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 352.0 ms (baseline 383.2 ms - TTFT also improves in this cell). tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.5581 from measured-window counters (792 draft / 442 accepted); run-variable across runs, this cell's patched medians 73.43 (n=5) and 77.14 (n=3 screen), samples 73.4-88.7 (band, not a point). POWER: 230 W CONFIGURED CAP; measured avg draw 228.60 W (xe hwmon energy1_input 2493763306 uJ over 10.909 s, bracketing the measured window only); 3.90 J/token over that window INCLUDING prefill; tokens/J 0.2566 vs 0.1952 baseline = +31.4%. RESULT 73.43 vs 52.61 tok/s = 1.40x (+39.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 1 tok of 517 = 0.19%); single variable = the two draft-INT4 env gates. Same-host re-runs +48.6% (p8192), +37.2/+44.4% (n=5), +46.0% (n=3 screen). Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal class. ENABLER: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM #54785 reports capture+MTP4 can give non-deterministic wrong logits at temp=0 (k<=3 clean); both arms capture-on so the A/B is consistent. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p512-n5-...-20260922T214938Z/.

Reactions

—

Submitted

Sep 22, 2026, 10:57 PM

Last edited

—

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

27B · Qwen

Intel Arc Pro B70 32GB
vllmGPTQ-Int448.81,729—4,738 ms0k
Show all details for Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

48.8 tok/s

Prefill

1,729 tok/s

Total

—

TTFT

4,738 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

8190

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (8190 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window (unique cold prompt with entropy nonce); 10/10 requests finished_reason=length at exactly 128 tokens

Notes

BASELINE ARM of a matched_with_tokenizer_delta A/B: GPTQ-INT4 g128 sym target + BF16 MTP4 drafter, drafter NOT quantized. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 8190 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 4738.1 ms. tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.4873 from measured-window counters (864 draft / 421 accepted); run-variable, 0.4873 this run vs 0.53-0.58 in the earlier baseline run - this run's baseline arm is at the low tail of acceptance and throughput, so the 1.49x here is the HIGH end of the reproduced +37.2/+44.4/+48.6% range. POWER: 230 W CONFIGURED CAP; measured avg draw 228.74 W (xe hwmon energy1_input 10730884522 uJ over 46.914 s, bracketing the measured window only); 16.77 J/token over that window INCLUDING prefill; tokens/J 0.0596 (vs 0.0654 patched = +9.6% for the patched arm). RESULT 48.81 vs 72.55 tok/s for the patched arm in this same cell = 1.49x (+48.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 4 tok of 8190 = 0.05%); single variable = the two draft-INT4 env gates. Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal emitted class; every emitted token target-verified. ENABLER for the patched effect: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM issue #54785 (2026-09-01) reports capture + MTP num_speculative_tokens=4 can give non-deterministic wrong logits at temperature=0 (k<=3 clean); both arms ran capture-on. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p8192-n5-...-20260922T213957Z/.

Reactions

—

Submitted

Sep 22, 2026, 10:56 PM

Last edited

—

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

27B · Qwen

Intel Arc Pro B70 32GB
vllmGPTQ-Int472.61,710—4,792 ms0k
Show all details for Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

72.6 tok/s

Prefill

1,710 tok/s

Total

—

TTFT

4,792 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

8194

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True -e B70_DRAFT_LMHEAD_INT4=1 -e B70_DRAFT_MTP_INT4=1 --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (8194 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window (unique cold prompt with entropy nonce); 10/10 requests finished_reason=length at exactly 128 tokens

Notes

THE IMPROVEMENT: draft-side INT4. Only the MTP drafter's weights are quantized (its 2.54 GB F16 LM head + the MTP body's 5 linears -> W4A16 g128 sym); the 27B target and its verification logits path are untouched. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 8194 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 4791.6 ms. tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.5676 from measured-window counters (784 draft / 445 accepted); run-variable across same-host runs 0.55-0.70 (this 0.5676); patched medians span 72.55-80.32, within-run samples 64.25-91.17 (band, not a point). POWER: 230 W CONFIGURED CAP; measured avg draw 229.50 W (xe hwmon energy1_input 9788913941 uJ over 42.654 s, bracketing the measured window only); 15.30 J/token over that window INCLUDING prefill; tokens/J 0.0654 vs 0.0596 baseline = +9.6%. RESULT 72.55 vs 48.81 tok/s = 1.49x (+48.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 4 tok of 8194 = 0.05%); single variable = the two draft-INT4 env gates. Same-host re-runs +39.6% (p512), +37.2/+44.4% (n=5), +46.0% (n=3 screen); a both-arms-patched control gave 80.61/78.27 tok/s. Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal emitted class. ENABLER: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM #54785 reports capture+MTP4 can give non-deterministic wrong logits at temp=0 (k<=3 clean); both arms capture-on so the A/B is consistent. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p8192-n5-...-20260922T213957Z/.

Reactions

—

Submitted

Sep 22, 2026, 10:55 PM

Last edited

—

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

27B · Qwen

Intel Arc Pro B70 32GB
vllmGPTQ-Int452.61,347—383 ms0k
Show all details for Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

52.6 tok/s

Prefill

1,347 tok/s

Total

—

TTFT

383 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

516

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (516 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window; 10/10 requests finished_reason=length at exactly 128 tokens

Notes

BASELINE ARM of a matched_with_tokenizer_delta A/B at the short-prompt cell: GPTQ-INT4 g128 sym target + BF16 MTP4 drafter, drafter NOT quantized. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 516 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 383.2 ms. tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.5435 from measured-window counters (804 draft / 437 accepted). POWER: 230 W CONFIGURED CAP; measured avg draw 224.53 W (xe hwmon energy1_input 3277950683 uJ over 14.599 s, bracketing the measured window only); 5.12 J/token over that window INCLUDING prefill; tokens/J 0.1952 (vs 0.2566 patched = +31.4% for the patched arm). RESULT 52.61 vs 73.43 tok/s for the patched arm in this same cell = 1.40x (+39.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 1 tok of 516 = 0.19%); single variable = the two draft-INT4 env gates. Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal emitted class; every emitted token target-verified. ENABLER for the patched effect: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM issue #54785 (2026-09-01) reports capture + MTP num_speculative_tokens=4 can give non-deterministic wrong logits at temperature=0 (k<=3 clean); both arms ran capture-on. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p512-n5-...-20260922T214938Z/.

Reactions

—

Submitted

Sep 22, 2026, 10:52 PM

Last edited

—

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

27B · Qwen

Intel Arc Pro B70 32GB
vllmGPTQ-Int473.41,469—352 ms0k
Show all details for Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

73.4 tok/s

Prefill

1,469 tok/s

Total

—

TTFT

352 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

517

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True -e B70_DRAFT_LMHEAD_INT4=1 -e B70_DRAFT_MTP_INT4=1 --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (517 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window; 10/10 requests finished_reason=length at exactly 128 tokens

Notes

THE IMPROVEMENT at the short-prompt cell: draft-side INT4. Only the MTP drafter's weights are quantized (its 2.54 GB F16 LM head + the MTP body's 5 linears -> W4A16 g128 sym); the 27B target and its verification logits path are untouched. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 517 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 352.0 ms, improved vs baseline 383.2 ms (NOT unchanged). tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.5581 from measured-window counters (792 draft / 442 accepted); run-variable 0.55-0.70 across same-host runs; patched medians span 72.55-80.32, within-run samples 64.25-91.17 (band, not a point). POWER: 230 W CONFIGURED CAP; measured avg draw 228.59 W (xe hwmon energy1_input 2493763306 uJ over 10.909 s, bracketing the measured window only); 3.89 J/token over that window INCLUDING prefill; tokens/J 0.2566 vs 0.1952 baseline = +31.4%. RESULT 73.43 vs 52.61 tok/s = 1.40x (+39.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 1 tok of 517 = 0.19%); single variable = the two draft-INT4 env gates. Same-host re-runs +48.6% (p8192), +37.2/+44.4% (n=5), +46.0% (n=3 screen). Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal class. ENABLER: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM #54785 reports capture+MTP4 can give non-deterministic wrong logits at temp=0 (k<=3 clean); both arms capture-on so the A/B is consistent. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p512-n5-...-20260922T214938Z/.

Reactions

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Submitted

Sep 22, 2026, 10:51 PM

Last edited

—

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

27B · Qwen

Intel Arc Pro B70 32GB
vllmGPTQ-Int448.81,729—4,738 ms0k
Show all details for Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

48.8 tok/s

Prefill

1,729 tok/s

Total

—

TTFT

4,738 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

8190

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (8190 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window (unique cold prompt with entropy nonce); 10/10 requests finished_reason=length at exactly 128 tokens

Notes

BASELINE ARM of a matched_with_tokenizer_delta A/B: GPTQ-INT4 g128 sym target + BF16 MTP4 drafter, drafter NOT quantized. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 8190 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 4738.1 ms. tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.4873 from measured-window counters (864 draft / 421 accepted); run-variable, 0.4873 this run vs 0.53-0.58 in the earlier baseline run - this run's baseline arm is at the low tail of acceptance and throughput, so the 1.49x here is the HIGH end of the reproduced +37.2/+44.4/+48.6% range. POWER: 230 W CONFIGURED CAP; measured avg draw 228.74 W (xe hwmon energy1_input 10730884522 uJ over 46.914 s, bracketing the measured window only); 16.77 J/token over that window INCLUDING prefill; tokens/J 0.0596 (vs 0.0654 patched = +9.6% for the patched arm). RESULT 48.81 vs 72.55 tok/s for the patched arm in this same cell = 1.49x (+48.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 4 tok of 8190 = 0.05%); single variable = the two draft-INT4 env gates. Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal emitted class; every emitted token target-verified. ENABLER for the patched effect: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM issue #54785 (2026-09-01) reports capture + MTP num_speculative_tokens=4 can give non-deterministic wrong logits at temperature=0 (k<=3 clean); both arms ran capture-on. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p8192-n5-...-20260922T213957Z/.

Reactions

—

Submitted

Sep 22, 2026, 10:50 PM

Last edited

—

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

27B · Qwen

Intel Arc Pro B70 32GB
vllmGPTQ-Int472.61,710—4,792 ms0k
Show all details for Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

72.6 tok/s

Prefill

1,710 tok/s

Total

—

TTFT

4,792 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

8194

Output tokens

128

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D

RAM

60GB

OS

Ubuntu 26.04.1 LTS

Power

230W

Engine

vllm

Engine version

0.27.2rc1.dev77+gac7509e2b

Quantization

GPTQ-Int4

Backend

xpu

Tensor parallel

1

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

yes

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

0.88

Max running seqs

8

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

yes

Spec method

MTP

Spec model

—

Spec draft model

—

Spec tokens

4

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

1

Temperature

0.7

Top P

0.8

Top K

20

Min P

—

Repeat penalty

—

Mirostat

—

Command

docker run -d --name b70-q38 -p 8000:8000 --device /dev/dri --group-add $(stat -c '%g' /dev/dri/render* | sort -u | head -1) -v /dev/dri:/dev/dri:ro -v <model_dir>:/model:ro -v patch_mtp_nightly.py:/patch_mtp.py:ro -v patch_mtp_boundary.py:/patch_boundary.py:ro -v champion_overlay/patch_gdn_fuse.py:/patch_gdn_fuse.py:ro -e VLLM_TARGET_DEVICE=xpu -e ZE_FLAT_DEVICE_HIERARCHY=COMPOSITE -e ZE_AFFINITY_MASK=1 -e VLLM_XPU_ENABLE_XPU_GRAPH=1 -e B70_MTP_BF16_DRAFT=1 -e PYTORCH_ALLOC_CONF=expandable_segments:True -e B70_DRAFT_LMHEAD_INT4=1 -e B70_DRAFT_MTP_INT4=1 --entrypoint bash vllm/vllm-openai-xpu@sha256:f01e24f6c7ff01f1e0662234255a1372297d1dbd89d003cf13c8fad3eab1ba4f -lc 'python /patch_mtp.py && python /patch_boundary.py && python /patch_gdn_fuse.py && exec vllm serve /model --quantization gptq --dtype float16 --language-model-only --trust-remote-code --kv-cache-dtype fp8 --max-model-len 16384 --gpu-memory-utilization 0.88 --max-num-seqs 8 --max-num-batched-tokens 8192 --no-enable-prefix-caching --served-model-name qwen38 --host 0.0.0.0 --port 8000 --speculative-config "{\"method\":\"mtp\",\"num_speculative_tokens\":4}"' # client: one HTTP stream at a time, ignore_eos, g128 all finish_reason=length, unique cold prompt with leading entropy nonce (8194 server-tokenizer tokens), one same-shape warmup discarded, n=5 post-warmup samples, median reported

Extra flags

--presence-penalty 1.5; one same-shape warmup discarded; prefix-cache hit delta zero across the measured window (unique cold prompt with entropy nonce); 10/10 requests finished_reason=length at exactly 128 tokens

Notes

THE IMPROVEMENT: draft-side INT4. Only the MTP drafter's weights are quantized (its 2.54 GB F16 LM head + the MTP body's 5 linears -> W4A16 g128 sym); the 27B target and its verification logits path are untouched. Metric: client post-first streaming rate (request-side), median of n=5 post-warmup; NOT engine-native tg. Coordinates: C1, actual 8194 prompt tokens (server tokenizer), g128 all finish_reason=length (640/640), cold_model_cold_prefix (prefix caching disabled, zero hit delta). TTFT median 4791.6 ms. tokSPrefill derived = promptTokens/TTFT (cold input rate = actual endpoint prompt tokens / client TTFT). Acceptance 0.5676 from measured-window counters (784 draft / 445 accepted); run-variable across same-host runs 0.55-0.70 (this 0.5676); patched medians span 72.55-80.32, within-run samples 64.25-91.17 (band, not a point). POWER: 230 W CONFIGURED CAP; measured avg draw 229.49 W (xe hwmon energy1_input 9788913941 uJ over 42.654 s, bracketing the measured window only); 15.29 J/token over that window INCLUDING prefill; tokens/J 0.0654 vs 0.0596 baseline = +9.6%. RESULT 72.55 vs 48.81 tok/s = 1.49x (+48.6%), n=5/arm median. Class matched_with_tokenizer_delta (arms' prompts differ 4 tok of 8194 = 0.05%); single variable = the two draft-INT4 env gates. Same-host re-runs +39.6% (p512), +37.2/+44.4% (n=5), +46.0% (n=3 screen); a both-arms-patched control gave 80.61/78.27 tok/s. Correctness: greedy byte-identical patched vs unpatched (3 prompts x 2 repeats); 30-draw x 6-prompt identical modal emitted class. ENABLER: XPU graph capture REQUIRED (capture off = inert <=1.5%; capture alone 1.68x); upstream vLLM #54785 reports capture+MTP4 can give non-deterministic wrong logits at temp=0 (k<=3 clean); both arms capture-on so the A/B is consistent. Stack uses local unpublished overlay patches; the image digest is public and pullable. PROVISIONAL self-report. Evidence: results/2026/09/b70-improvement-probes-20260920/p4-champion-ab-p8192-n5-...-20260922T213957Z/.

Reactions

—

Submitted

Sep 22, 2026, 10:48 PM

Last edited

—

Qwen3.8-Flash-Next-GGUF

180B MoE · Qwen

Intel Arc Pro B70 32GB ×2
llama.cppQ4_K_M (AD-4.27bpw M64 dynamic)33.3173——0k
Show all details for Qwen3.8-Flash-Next-GGUF

Model

AtomicChat/Qwen3.8-Flash-Next-GGUF

Display name

Qwen3.8-Flash-Next-GGUF

Base model

Qwen3.8-Flash-Next

Revision

main

Family

Qwen

Parameters

180B

Active params

—

MoE

yes

Output

33.3 tok/s

Prefill

173 tok/s

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

0

Output tokens

0

Prefill tokens

0

Context length

8192

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB ×2

GPU slots

—

GPU count

2

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (6 decode / 14 batch threads)

RAM

60GB

OS

Linux

Power

195W

Engine

llama.cpp

Engine version

SYCL 0.3.0-dev @ 52d4268 + qwen4exp MTP port + local multi-token verify kernel

Quantization

Q4_K_M (AD-4.27bpw M64 dynamic)

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

99

Split mode

layer

KV cache dtype

q8_0/q4_1

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

yes

Chunked prefill

—

Prefill chunk

512

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

1

Concurrency

—

Spec decoding

yes

Spec method

MTP

Spec model

Qwen3.8-Flash-Next-MTP-Q4_K_M.gguf

Spec draft model

—

Spec tokens

3

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

—

Temperature

6

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

LLAMA_ATTN_ROT_DISABLE=1 llama-server -m Qwen3.8-Flash-Next-AD-4.27bpw-Q4_K_M-M64.gguf -md Qwen3.8-Flash-Next-MTP-Q4_K_M.gguf -ngld 999 --spec-type draft-mtp --spec-draft-n-max 3 --spec-draft-p-min 0.75 --spec-draft-backend-sampling --spec-draft-device SYCL1 --device SYCL0,SYCL1 --tensor-split 1,1 --split-mode layer -ngl 99 -ot per_layer_token_embd=CPU -fa on -t 6 -tb 14 -np 1 -c 8192 -b 512 --ubatch-size 512 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Extra flags

--ngld 999 --spec-draft-p-min 0.75 --spec-draft-backend-sampling --spec-draft-device SYCL1 --tensor-split 1,1 --ot per_layer_token_embd=CPU --tb 14 --b 512 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Notes

Qwen3.8-Flash-Next 125B-A6B MoE + 51B n-gram PLE table (35.76 GiB Q5_1) mmap host, page-cache pre-warmed. Quant: AtomicChat AD-4.27bpw Q4_K_M M64 + dzannotti MTP draft head Q4_K_M. Self-measured engine-native C1, single client, 195 W cap, sampling t=1.0/top_p 0.95/top_k 20, ignore_eos, zero cache reuse, exact token counts. Local multi-token MoE kernel (fused MUL_MAT_ID for M=2..8, both gate_up and grouped down forms) wired into llama.cpp SYCL 52d4268 + qwen4exp MTP port; round cost 118->~85 ms vs unpatched. Long context: c16 P~8.5K prose 30.85 median decode / 412 cold input (n=5); c131072 near-boundary P~120K completed n=5 (first on this host): 18.38 median decode / 222.9 cold input, capacity-observation tier. Acceptance 79-83% on matched natural prompts (code > prose); quality battery 42/42, divergence inside spec-OFF envelope. PROVISIONAL self-report, not independently reproduced.

Reactions

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Submitted

Sep 11, 2026, 1:05 PM

Last edited

—

Qwen3.8-Flash-Next-GGUF

180B MoE · Qwen

Intel Arc Pro B70 32GB ×2
llama.cppQ4_K_M (AD-4.27bpw M64 dynamic)23.0586——0k
Show all details for Qwen3.8-Flash-Next-GGUF

Model

AtomicChat/Qwen3.8-Flash-Next-GGUF

Display name

Qwen3.8-Flash-Next-GGUF

Base model

Qwen3.8-Flash-Next

Revision

main

Family

Qwen

Parameters

180B

Active params

—

MoE

yes

Output

23.0 tok/s

Prefill

586 tok/s

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

0

Output tokens

0

Prefill tokens

0

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB ×2

GPU slots

—

GPU count

2

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (6 decode / 14 batch threads)

RAM

60GB

OS

Linux

Power

195W

Engine

llama.cpp

Engine version

SYCL 0.3.0-dev @ 52d4268, GGML_SYCL_F16=ON build

Quantization

Q4_K_M (AD-4.27bpw M64 dynamic)

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

99

Split mode

layer

KV cache dtype

q8_0/q4_1

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

yes

Chunked prefill

—

Prefill chunk

3072

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

1

Concurrency

—

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

6

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

llama-server -m Qwen3.8-Flash-Next-AD-4.27bpw-Q4_K_M-M64.gguf --device SYCL0,SYCL1 --tensor-split 1,1 --split-mode layer -ngl 99 -ot per_layer_token_embd=CPU -fa on -t 6 -tb 14 -np 1 -c 16384 -b 3072 --ubatch-size 3072 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Extra flags

--tensor-split 1,1 --ot per_layer_token_embd=CPU --tb 14 --b 3072 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Notes

Prefill record (separate from decode record by design: different binary/spec). Quant: AtomicChat AD-4.27bpw Q4_K_M M64 GGUF. F16-accumulation binary is worth ~+38% vs FP32 at b3072. Self-measured engine-native C1, single client, n=3 median, P9096(actual)/G128/C1 COLD INPUT rate (llama.cpp HTTP full uncached prompt, not llama-bench pp), zero prompt-cache reuse verified per sample, stdev 0.2. Decode in same cell 22.96 tok/s (no-spec F16). PLE table mmap host. PROVISIONAL self-report, not independently reproduced.

Reactions

—

Submitted

Sep 11, 2026, 6:15 AM

Last edited

—

Qwen3.8-Flash-Next-GGUF

180B MoE · Qwen

Intel Arc Pro B70 32GB ×2
llama.cppQ4_K_M (AD-4.27bpw M64 dynamic)27.7173——0k
Show all details for Qwen3.8-Flash-Next-GGUF

Model

AtomicChat/Qwen3.8-Flash-Next-GGUF

Display name

Qwen3.8-Flash-Next-GGUF

Base model

Qwen3.8-Flash-Next

Revision

main

Family

Qwen

Parameters

180B

Active params

—

MoE

yes

Output

27.7 tok/s

Prefill

173 tok/s

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

0

Output tokens

0

Prefill tokens

0

Context length

8192

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB ×2

GPU slots

—

GPU count

2

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (6 decode / 14 batch threads)

RAM

60GB

OS

Linux

Power

195W

Engine

llama.cpp

Engine version

SYCL 0.3.0-dev @ 52d4268 + qwen4exp MTP port + local multi-token verify kernel

Quantization

Q4_K_M (AD-4.27bpw M64 dynamic)

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

99

Split mode

layer

KV cache dtype

q8_0/q4_1

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

yes

Chunked prefill

—

Prefill chunk

512

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

1

Concurrency

—

Spec decoding

yes

Spec method

MTP

Spec model

Qwen3.8-Flash-Next-MTP-Q4_K_M.gguf

Spec draft model

—

Spec tokens

3

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

yes

MTP draft layers

—

Temperature

6

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

LLAMA_ATTN_ROT_DISABLE=1 llama-server -m Qwen3.8-Flash-Next-AD-4.27bpw-Q4_K_M-M64.gguf -md Qwen3.8-Flash-Next-MTP-Q4_K_M.gguf -ngld 999 --spec-type draft-mtp --spec-draft-n-max 3 --spec-draft-p-min 0.75 --spec-draft-backend-sampling --spec-draft-device SYCL1 --device SYCL0,SYCL1 --tensor-split 1,1 --split-mode layer -ngl 99 -ot per_layer_token_embd=CPU -fa on -t 6 -tb 14 -np 1 -c 8192 -b 512 --ubatch-size 512 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Extra flags

--ngld 999 --spec-draft-p-min 0.75 --spec-draft-backend-sampling --spec-draft-device SYCL1 --tensor-split 1,1 --ot per_layer_token_embd=CPU --tb 14 --b 512 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Notes

Qwen3.8-Flash-Next 125B-A6B MoE (48L: 36 GDN + 12 QSA, 512 experts top-10) + 51B n-gram PLE table (35.76 GiB Q5_1) mmap host, page-cache pre-warmed. Quant: AtomicChat AD-4.27bpw Q4_K_M M64 GGUF + dzannotti MTP draft head Q4_K_M (-md). Self-measured engine-native C1 timing (not client-side), single client, n=5 fresh-server median, P512(actual)/G128/C1, range 22.63-28.88 (unwarmed twin 26.33; warm-server n=3 29.90). MTP acceptance 87.7% (13,156/14,996, 7,158 rounds) on natural prose+code; quality battery 42/42 code tests, divergence inside spec-OFF envelope. MTP needs local qwen4exp port (not upstream at 52d4268); LLAMA_ATTN_ROT_DISABLE=1 mandatory with quantized KV. PROVISIONAL self-report, not independently reproduced. Prefill 512-cell cold input 173 tok/s; long-prompt prefill is a separate record.

Reactions

—

Submitted

Sep 11, 2026, 6:15 AM

Last edited

—

Qwen3.8-Flash-Next

180B · Qwen

Intel Arc Pro B70 32GB ×2
llama.cppIQ3_S20.3594———
Show all details for Qwen3.8-Flash-Next

Model

Qwen/Qwen3.8-Flash-Next

Display name

Qwen3.8-Flash-Next

Base model

—

Revision

main

Family

Qwen

Parameters

180B

Active params

—

MoE

no

Output

20.3 tok/s

Prefill

594 tok/s

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

0

Output tokens

0

Prefill tokens

—

Context length

16384

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB ×2

GPU slots

—

GPU count

2

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

—

RAM

—

OS

Linux

Power

—

Engine

llama.cpp

Engine version

0.3.0-dev b492 9723942 SYCL F16=ON

Quantization

IQ3_S

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

99

Split mode

layer

KV cache dtype

q8_0/q4_1

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

yes

Chunked prefill

—

Prefill chunk

3072

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

1

Concurrency

—

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

6

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

llama-server -m Qwen3.8-Flash-Next-AD-4.27bpw-Q4_K_M-M64-00001-of-00033.gguf --device SYCL0,SYCL1 --tensor-split 1,1 --split-mode layer -ngl 99 -ot per_layer_token_embd=CPU -c 16384 -fa on -t 6 -tb 14 -np 1 -b 3072 --ubatch-size 3072 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Extra flags

--tensor-split 1,1 --ot per_layer_token_embd=CPU --tb 14 --b 3072 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Notes

C1 only (-np 1, one client). c16 means context 16384, not concurrency 16. Prefill = llama.cpp engine timings.prompt_per_second median n=5 at actual p9096/g128, fused IQ3_S/IQ4_NL MMVQ, GGML_SYCL_F16=ON, -b/-ub 3072, cache_n=0. Decode on this same F16 server is 20.34, not the fused-FP32 23.38 cell. Artifact AtomicChat Qwen3.8-Flash-Next-AD-4.27bpw-Q4_K_M-M64 rev 142262902a46f7daed19c79d0771534c8106ad59. Mixed: gate/up IQ3_S, down IQ4_NL, PLE Q5_1 CPU mmap (platform quantization field is IQ3_S). KV q8_0/q4_1, FA on, layer split 1,1, 195 W configured cap. Loaded-idle GPU1 pkg ~62 C. E2 self-report. Independent reproduction pending. Patches: patches/llamacpp-sycl/flashnext-arch-overlay.patch then sycl-fused-mmvq-and-gpu-group.patch.

Reactions

—

Submitted

Sep 1, 2026, 9:24 AM

Last edited

—

Qwen3.8-Flash-Next

180B · Qwen

Intel Arc Pro B70 32GB ×2
llama.cppIQ3_S23.4184———
Show all details for Qwen3.8-Flash-Next

Model

Qwen/Qwen3.8-Flash-Next

Display name

Qwen3.8-Flash-Next

Base model

—

Revision

main

Family

Qwen

Parameters

180B

Active params

—

MoE

no

Output

23.4 tok/s

Prefill

184 tok/s

Total

—

TTFT

—

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

0

Output tokens

0

Prefill tokens

—

Context length

8192

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB ×2

GPU slots

—

GPU count

2

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

—

RAM

—

OS

Linux

Power

—

Engine

llama.cpp

Engine version

0.3.0-dev b492 9723942 SYCL F16=OFF

Quantization

IQ3_S

Backend

xpu

Tensor parallel

—

Pipeline parallel

—

GPU layers

99

Split mode

layer

KV cache dtype

q8_0/q4_1

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

yes

Chunked prefill

—

Prefill chunk

512

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

1

Concurrency

—

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

6

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

llama-server -m Qwen3.8-Flash-Next-AD-4.27bpw-Q4_K_M-M64-00001-of-00033.gguf --device SYCL0,SYCL1 --tensor-split 1,1 --split-mode layer -ngl 99 -ot per_layer_token_embd=CPU -c 8192 -fa on -t 6 -tb 14 -np 1 -b 512 --ubatch-size 512 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Extra flags

--tensor-split 1,1 --ot per_layer_token_embd=CPU --tb 14 --b 512 --cache-type-k q8_0 --cache-type-v q4_1 --no-warmup --no-cache-prompt

Notes

C1 only (-np 1, one client). c8 means context 8192, not concurrency 8. Decode = llama.cpp engine timings.predicted_per_second median n=5 at p512/g128, fused IQ3_S/IQ4_NL MMVQ, GGML_SYCL_F16=OFF. Cold input = timings.prompt_per_second with cache_n=0 (183.98). Do not mix this decode number with the fused-F16 594.49 prefill cell (separate binary). Artifact AtomicChat Qwen3.8-Flash-Next-AD-4.27bpw-Q4_K_M-M64 rev 142262902a46f7daed19c79d0771534c8106ad59. Mixed: gate/up IQ3_S, down IQ4_NL, PLE Q5_1 CPU mmap (platform quantization field is IQ3_S). KV q8_0/q4_1, FA on, layer split 1,1, 195 W configured cap. Loaded-idle GPU1 pkg ~62 C, not ordinary <=55 C. E2 self-report. Independent reproduction pending. Patches: patches/llamacpp-sycl/flashnext-arch-overlay.patch then sycl-fused-mmvq-and-gpu-group.patch.

Reactions

—

Submitted

Sep 1, 2026, 9:24 AM

Last edited

—

Qwen3.8-27B-FP8

27B · Qwen

Intel Arc Pro B70 32GB ×2
vllmFP831.139039.4190 ms—
Show all details for Qwen3.8-27B-FP8

Model

Qwen/Qwen3.8-27B-FP8

Display name

Qwen3.8-27B-FP8

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

31.1 tok/s

Prefill

390 tok/s

Total

39.4 tok/s

TTFT

190 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

74

Output tokens

256

Prefill tokens

—

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB ×2

GPU slots

—

GPU count

2

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

FP8

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

—

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8920 servedModel: qw38-fp8

Extra flags

—

Notes

—

Reactions

—

Submitted

Aug 30, 2026, 6:06 PM

Last edited

—

Qwen3.8-27B-FP8

27B · Qwen

Intel Arc Pro B70 32GB ×2
vllmFP828.636136.2205 ms—
Show all details for Qwen3.8-27B-FP8

Model

Qwen/Qwen3.8-27B-FP8

Display name

Qwen3.8-27B-FP8

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

28.6 tok/s

Prefill

361 tok/s

Total

36.2 tok/s

TTFT

205 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

74

Output tokens

256

Prefill tokens

—

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB ×2

GPU slots

—

GPU count

2

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

FP8

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

—

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8920 servedModel: qw38-fp8

Extra flags

—

Notes

—

Reactions

—

Submitted

Aug 30, 2026, 4:04 PM

Last edited

—

Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

3B MoE · Qwen

Intel Arc Pro B70 32GB
vllmGPTQ-Int41089,0732,034320 ms—
Show all details for Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

Model

SergiioB/Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

Display name

Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

Base model

Ornith-1.5-35B-A3B

Revision

main

Family

Qwen

Parameters

35B

Active params

3B

MoE

yes

Output

108 tok/s

Prefill

9,073 tok/s

Total

2,034 tok/s

TTFT

320 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

2906

Output tokens

128

Prefill tokens

—

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

GPTQ-Int4

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

—

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8000 servedModel: ornith15

Extra flags

—

Notes

—

Reactions

—

Submitted

Aug 21, 2026, 10:36 AM

Last edited

—

Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

3B MoE · Qwen

Intel Arc Pro B70 32GB
vllmGPTQ-Int469.99,7801,435297 ms—
Show all details for Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

Model

SergiioB/Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

Display name

Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

Base model

Ornith-1.5-35B-A3B

Revision

main

Family

Qwen

Parameters

35B

Active params

3B

MoE

yes

Output

69.9 tok/s

Prefill

9,780 tok/s

Total

1,435 tok/s

TTFT

297 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

2906

Output tokens

128

Prefill tokens

—

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

GPTQ-Int4

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

—

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8000 servedModel: ornith15

Extra flags

—

Notes

—

Reactions

—

Submitted

Aug 21, 2026, 10:18 AM

Last edited

—

Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

3B MoE · Qwen

Intel Arc Pro B70 32GB
vllmGPTQ-Int494.165510448.9 ms—
Show all details for Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

Model

SergiioB/Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

Display name

Ornith-1.5-35B-A3B-GPTQ-Int4-sym-G128-MTP-BF16-MixedCal-v2

Base model

Ornith-1.5-35B-A3B

Revision

main

Family

Qwen

Parameters

35B

Active params

3B

MoE

yes

Output

94.1 tok/s

Prefill

655 tok/s

Total

104 tok/s

TTFT

48.9 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

32

Output tokens

256

Prefill tokens

—

Context length

2048

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

150W

Engine

vllm

Engine version

—

Quantization

GPTQ-Int4

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

—

KV cache size

—

Prefix caching

—

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8000 servedModel: ornith15

Extra flags

—

Notes

—

Reactions

—

Submitted

Aug 21, 2026, 10:14 AM

Last edited

—

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

27B · Qwen

Intel Arc Pro B70 32GB
vllmGPTQ-Int41081,69470.824,360 ms—
Show all details for Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

108 tok/s

Prefill

1,694 tok/s

Total

70.8 tok/s

TTFT

24,360 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

74

Output tokens

256

Prefill tokens

—

Context length

131072

Batch size

5

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

GPTQ-Int4

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

yes

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

5

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8000 servedModel: qwen38

Extra flags

—

Notes

Single Intel Arc Pro B70 32GB. Stack: vLLM XPU nightly f01e24f6, MTP4, GDN mixed-split v5, draft-INT4 S+M1, prefix caching ON. Realistic 5-user coding serving at the Qwen3.8-27B model-card RECOMMENDED non-thinking sampling (temperature=0.7, top_p=0.80, top_k=20, presence_penalty=1.5). 5 concurrent multi-turn coding sessions, ~8K session prompts, 512-token generations, 45/45 OK, real completions in history. tokSOut = sum of per-stream rates (5 x 21.6 median per-user tok/s). Per-turn Sigma: t1 134.4 / t2 106.3 / t3 100.5. TTFT 21-26s per turn (prefix cache lands 0-38% of shared tokens at C5 on this build). MTP acceptance 34-41% under concurrency. Greedy sibling: 127.4 Sigma.

Reactions

—

Submitted

Aug 19, 2026, 1:39 PM

Last edited

—

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

27B · Qwen

Intel Arc Pro B70 32GB
vllmGPTQ-Int41031,69470.8337 ms—
Show all details for Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

103 tok/s

Prefill

1,694 tok/s

Total

70.8 tok/s

TTFT

337 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

74

Output tokens

256

Prefill tokens

—

Context length

131072

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

GPTQ-Int4

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

yes

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8000 servedModel: qwen38

Extra flags

—

Notes

Single Intel Arc Pro B70 32GB. Stack: vLLM XPU nightly f01e24f6, MTP4, GDN mixed-split v5, draft-INT4 S+M1, prefix caching ON. Qwen3.8-27B model-card RECOMMENDED non-thinking sampling: temperature=0.7, top_p=0.80, top_k=20, presence_penalty=1.5. C1 client post-first, n=5 median 102.61 (95.7-106.7), calibrated real-world Pi prompts, MTP acceptance 91.8%. Greedy sibling on the same stack: 106.7 (93% acceptance) - recommended sampling costs ~4% here. Cold input 1694 tok/s p8192/g1.

Reactions

—

Submitted

Aug 19, 2026, 1:39 PM

Last edited

—

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

27B · Qwen

Intel Arc Pro B70 32GB
vllmGPTQ-Int41271,69470.822,850 ms—
Show all details for Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

127 tok/s

Prefill

1,694 tok/s

Total

70.8 tok/s

TTFT

22,850 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

74

Output tokens

256

Prefill tokens

—

Context length

131072

Batch size

5

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

GPTQ-Int4

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

yes

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8000 servedModel: qwen38

Extra flags

—

Notes

Self-reported. Single Intel Arc Pro B70 32GB. Realistic 5-user coding serving, v2 with REAL completions kept in session history (supersedes the stubbed same-day 138.3 record). Stack: vLLM XPU nightly f01e24f6, MTP4, GDN mixed-split v5, draft-INT4 S+M1, prefix caching ON. 5 concurrent sessions, ~8K start, 3 turns, g512, 60/60 OK. tokSOut = sum of per-stream generation rates (5 x 25.5 median per-user tok/s, all turns). Per-turn: t1 165.5, t2 127.9, t3 114.2 aggregate. TTFT 22.6-25.0s every turn: prefix cache lands 0-38% of shared tokens at C5 on this build (vs 91% at C1), so ~45-53K session tokens re-prefill per turn. MTP acceptance 43-56% under concurrency. Short-prompt C5 (203.8) is a separate record; C1 is 106.7.

Reactions

—

Submitted

Aug 19, 2026, 12:59 PM

Last edited

—

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

27B · Qwen

Intel Arc Pro B70 32GB
vllmGPTQ-Int41071,69470.8335 ms—
Show all details for Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Model

SergiioB/Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Display name

Qwen3.8-27B-GPTQ-Int4-sym-G128-MTP-BF16

Base model

Qwen3.8-27B

Revision

main

Family

Qwen

Parameters

27B

Active params

—

MoE

no

Output

107 tok/s

Prefill

1,694 tok/s

Total

70.8 tok/s

TTFT

335 ms

Peak VRAM

—

Power draw

—

Hardware cost

—

Prompt tokens

74

Output tokens

256

Prefill tokens

—

Context length

131072

Batch size

1

Hardware class

DISCRETE_GPU

Hardware

Intel Arc Pro B70 32GB

GPU slots

—

GPU count

1

VRAM

32GB

Chip vendor

—

Chip family

—

Chip variant

—

Unified memory

—

NPU TOPS

—

CPU

AMD Ryzen 7 5700X3D (8 threads)

RAM

30GB

OS

Linux

Power

230W

Engine

vllm

Engine version

—

Quantization

GPTQ-Int4

Backend

cuda

Tensor parallel

—

Pipeline parallel

—

GPU layers

—

Split mode

—

KV cache dtype

fp8

KV cache size

—

Prefix caching

yes

Attention backend

—

Flash attention

—

Chunked prefill

—

Prefill chunk

—

Continuous batching

—

CPU offload

—

CPU layers

—

Rope scaling

—

Rope scale

—

Yarn ext factor

—

Engine quant

—

SGLang quant

—

GPU mem util

—

Max running seqs

—

Scheduler delay

—

Num parallel

—

Concurrency

1

Spec decoding

no

Spec method

—

Spec model

—

Spec draft model

—

Spec tokens

—

Spec ngram

—

Spec draft TP

—

Spec draft window

—

MTP enabled

no

MTP draft layers

—

Temperature

—

Top P

—

Top K

—

Min P

—

Repeat penalty

—

Mirostat

—

Command

# Remote endpoint: http://127.0.0.1:8000 servedModel: qwen38

Extra flags

—

Notes

Self-reported. Single Intel Arc Pro B70 32GB. Current full stack: vLLM XPU nightly f01e24f6, MTP4, GDN mixed-split v5, draft-INT4 S+M1, prefix caching ON (zero hits, unique prompts). C1 client post-first, n=5 median 106.7 (103.2-111.3), calibrated real-world Pi prompt set; MTP acceptance 89-96%; cold input 1694 tok/s at p8192/g1. Supersedes same-day 100.2 (same config, run-to-run variance). Cache-off sibling record: 112.65. Degenerate INDEX filler measures ~71 (44% acceptance) - prompt family matters.

Reactions

—

Submitted

Aug 19, 2026, 12:59 PM

Last edited

—