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SergiioB

SergiioB

@SergiioB · Member since 2026

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Mainly llama.cpp 21 approved runs

Submissions

21

Models

9

Avg out

66.8

Avg prefill

643.7

Avg total

95.1

Avg TTFT

117.5ms

HW configs

1

Personal bests9

Fastest approved result for each model.

06 runs
Output164.5 tok/s
Prefill383.4 tok/s
TTFT
Depth
Intel Arc Pro B70 32GB

llama.cpp · Q5_K_M · 1w ago

01 run
Output145.9 tok/s
Prefill
TTFT
Depth
Intel Arc Pro B70 32GB

llama.cpp · Q5_K_M · 1w ago

35B MoE2 runs
Output73.2 tok/s
Prefill416.1 tok/s
TTFT77ms
Depth
Intel Arc Pro B70 32GB

llama.cpp · Q4_K_M · 2w ago

3B MoE2 runs
Output67.0 tok/s
Prefill464.9 tok/s
TTFT69ms
Depth
Intel Arc Pro B70 32GB

llama.cpp · Q5_K_M · 2w ago

35B2 runs
Output62.8 tok/s
Prefill1682.4 tok/s
TTFT
Depth
Intel Arc Pro B70 32GB

llama.cpp · Q4_K_XL · today

02 runs
Output50.3 tok/s
Prefill553.9 tok/s
TTFT58ms
Depth
Intel Arc Pro B70 32GB

llama.cpp · Q6_K · 2w ago

28B2 runs
Output29.7 tok/s
Prefill102.4 tok/s
TTFT312ms
Depth
Intel Arc Pro B70 32GB

llama.cpp · Q5_K_M · 2w ago

33B3 runs
Output26.6 tok/s
Prefill384.8 tok/s
TTFT
Depth
Intel Arc Pro B70 32GB

llama.cpp · Q4_K_M · today

28B1 run
Output25.1 tok/s
Prefill613.0 tok/s
TTFT
Depth
Intel Arc Pro B70 32GB

llama.cpp · Q5_K_M · today

All runs21

Full approved benchmark history.

gemma-4-31B-it

33B · Gemma

26.6

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q4_K_M

TTFT

Context

131k · today

Show all run details

Model

google/gemma-4-31B-it

Display name

gemma-4-31B-it

Base model

gemma-4-31B

Revision

main

Family

Gemma

Parameters

33B

Active params

MoE

no

Output tok/s

26.6

Prefill tok/s

384.8

Total tok/s

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q4_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q8_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m gemma-4-31B-it-Q4_K_M.gguf --spec-type draft-mtp --spec-draft-model mtp-gemma-4-31B-it.gguf --spec-draft-n-max 4 -fa on -ctk q8_0 -ctv q4_1 -c 131072 -b 8192 -ub 4096

Extra flags

--spec-type draft-mtp --spec-draft-model mtp-gemma-4-31B-it.gguf --spec-draft-n-max 4 --ctk q8_0 --ctv q4_1 --b 8192

Notes

Gemma-4-31B-it Q4_K_M + MTP-4 @180W best dense decode in sweep. Prefill ~4k. 2026-07-16.

Reactions

Submitted

Jul 16, 2026, 9:49 AM

Last edited

gemma-4-31B-it

33B · Gemma

24.8

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q4_K_M

TTFT

Context

131k · today

Show all run details

Model

google/gemma-4-31B-it

Display name

gemma-4-31B-it

Base model

gemma-4-31B

Revision

main

Family

Gemma

Parameters

33B

Active params

MoE

no

Output tok/s

24.8

Prefill tok/s

361.2

Total tok/s

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q4_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q8_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m gemma-4-31B-it-Q4_K_M.gguf --spec-type draft-mtp --spec-draft-model mtp-gemma-4-31B-it.gguf --spec-draft-n-max 4 -fa on -ctk q8_0 -ctv q4_1 -c 131072 -b 8192 -ub 4096

Extra flags

--spec-type draft-mtp --spec-draft-model mtp-gemma-4-31B-it.gguf --spec-draft-n-max 4 --ctk q8_0 --ctv q4_1 --b 8192

Notes

Gemma-4-31B-it Q4_K_M + Unsloth mtp-gemma-4-31B-it draft-mtp n-max 4 @165W. Decode +51% vs base. Prefill ~4k. 2026-07-16.

Reactions

Submitted

Jul 16, 2026, 9:49 AM

Last edited

gemma-4-31B-it

33B · Gemma

16.4

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q4_K_M

TTFT

Context

131k · today

Show all run details

Model

google/gemma-4-31B-it

Display name

gemma-4-31B-it

Base model

gemma-4-31B

Revision

main

Family

Gemma

Parameters

33B

Active params

MoE

no

Output tok/s

16.4

Prefill tok/s

332.9

Total tok/s

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q4_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q8_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m gemma-4-31B-it-Q4_K_M.gguf -fa on -ctk q8_0 -ctv q4_1 -c 131072 -b 8192 -ub 4096

Extra flags

--ctk q8_0 --ctv q4_1 --b 8192

Notes

Gemma-4-31B-it Q4_K_M BASE no MTP @150W. Single-stream dense control. Prefill ~4k. 2026-07-16.

Reactions

Submitted

Jul 16, 2026, 9:49 AM

Last edited

Qwen3.5-27B

28B · Qwen

25.1

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q5_K_M

TTFT

Context

205k · today

Show all run details

Model

Qwen/Qwen3.5-27B

Display name

Qwen3.5-27B

Base model

Revision

main

Family

Qwen

Parameters

28B

Active params

MoE

no

Output tok/s

25.1

Prefill tok/s

613.0

Total tok/s

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

Prefill tokens

Context length

204800

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q8_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Qwen3.6-27B-MTP-Q5_K_M.gguf --spec-type draft-mtp --spec-draft-n-max 4 -fa on -ctk q8_0 -ctv q4_1 -c 204800 -b 8192 -ub 4096

Extra flags

--spec-type draft-mtp --spec-draft-n-max 4 --ctk q8_0 --ctv q4_1 --b 8192

Notes

Qwen3.6-27B-MTP-Q5_K_M dense + draft-mtp n-max 4. Single-stream. Prefill ~4k. Profile qwen27-mtp-q5-256k-165w @165W. 2026-07-16.

Reactions

Submitted

Jul 16, 2026, 9:49 AM

Last edited

Qwen3.5-35B-A3B

35B · Qwen

62.8

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q4_K_XL

TTFT

Context

262k · today

Show all run details

Model

Qwen/Qwen3.5-35B-A3B

Display name

Qwen3.5-35B-A3B

Base model

Qwen3.5-35B-A3B-Base

Revision

main

Family

Qwen

Parameters

35B

Active params

MoE

no

Output tok/s

62.8

Prefill tok/s

1682.4

Total tok/s

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q4_K_XL

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q8_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Qwen3.6-35B-A3B-UD-Q4_K_XL.gguf -ngl 99 -ncmoe 0 -fa on -ctk q8_0 -ctv q4_1 -c 262144 -b 8192 -ub 4096

Extra flags

--ncmoe 0 --ctk q8_0 --ctv q4_1 --b 8192

Notes

Qwen3.6-35B-A3B UD-Q4_K_XL. Single-stream. Prefill ~4k. Profile qwen35-q4-256k. 2026-07-16.

Reactions

Submitted

Jul 16, 2026, 9:49 AM

Last edited

Qwen3.5-35B-A3B

35B · Qwen

61.5

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q5_K_M

TTFT

Context

262k · today

Show all run details

Model

Qwen/Qwen3.5-35B-A3B

Display name

Qwen3.5-35B-A3B

Base model

Qwen3.5-35B-A3B-Base

Revision

main

Family

Qwen

Parameters

35B

Active params

MoE

no

Output tok/s

61.5

Prefill tok/s

1690.2

Total tok/s

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q8_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Qwen3.6-35B-A3B-UD-Q5_K_M.gguf -ngl 99 -ncmoe 0 -fa on -ctk q8_0 -ctv q4_1 -c 262144 -b 8192 -ub 4096

Extra flags

--ncmoe 0 --ctk q8_0 --ctv q4_1 --b 8192

Notes

Qwen3.6-35B-A3B UD-Q5_K_M GGUF served as active. Single-stream. Prefill ~4k tokens. Profile qwen35-q5-256k. 2026-07-16.

Reactions

Submitted

Jul 16, 2026, 9:49 AM

Last edited

69.3

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q5_K_M

TTFT

Context

262k · today

Show all run details

Model

deepreinforce-ai/Ornith-1.0-35B

Display name

Ornith-1.0-35B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

yes

Output tok/s

69.3

Prefill tok/s

1725.9

Total tok/s

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q8_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-35b-Q5_K_M.gguf -ngl 99 -ncmoe 0 -fa on -ctk q8_0 -ctv q4_1 -c 262144 -b 8192 -ub 4096 -dev SYCL0

Extra flags

--ncmoe 0 --ctk q8_0 --ctv q4_1 --b 8192 --dev SYCL0

Notes

Single-stream SYCL llama-server. Decode from generation task; prefill from ~4k prompt timings.prompt_per_second. -b8192 -ub4096 FA on ctk q8_0 ctv q4_1. Profile ornith35-q5-256k. 2026-07-16.

Reactions

Submitted

Jul 16, 2026, 9:49 AM

Last edited

67.6

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q5_K_M

TTFT

Context

131k · 1w ago

Show all run details

Model

deepreinforce-ai/Ornith-1.0-35B

Display name

Ornith-1.0-35B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

yes

Output tok/s

67.6

Prefill tok/s

1242.3

Total tok/s

67.6

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q5_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-35b-Q5_K_M.gguf --parallel 1 --ctx-size 131072 -fa on -ctk q5_0 -ctv q4_1 -b 8192 -ub 4096

Extra flags

--ctk q5_0 --ctv q4_1 --b 8192

Notes

PEAK SINGLE-STREAM PREFILL TEST: Measured using a contiguous 3000-token prompt block without concurrency (batch=1). Uncovers the raw 1,242 tok/s prefill capacity of the B70 without the massive context-switching overhead incurred in fleet concurrency. Hardware capped at optimal 165W/2400MHz.

Reactions

Submitted

Jul 6, 2026, 9:41 AM

Last edited

164.5

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q5_K_M

TTFT

Context

131k · 1w ago

Show all run details

Model

deepreinforce-ai/Ornith-1.0-35B

Display name

Ornith-1.0-35B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

yes

Output tok/s

164.5

Prefill tok/s

383.4

Total tok/s

171.1

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

Prefill tokens

Context length

131072

Batch size

32

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q5_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

32

Concurrency

Spec decoding

no

Spec method

Spec model

Spec draft model

Spec tokens

Spec ngram

Spec draft TP

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-35b-Q5_K_M.gguf --parallel 32 --ctx-size 131072 -fa on -ctk q5_0 -ctv q4_1 -b 8192 -ub 4096

Extra flags

--ctk q5_0 --ctv q4_1 --b 8192

Notes

POWER/FREQUENCY UNLOCKED TEST: max_freq pushed to 2800 MHz, power1_cap relaxed to 230W. Telemetry logged 196W sustained draw at 73C. Memory bandwidth bottleneck confirmed: +33% power yielded only +8% throughput over the 165W/2400MHz baseline.

Reactions

Submitted

Jul 6, 2026, 9:33 AM

Last edited

153.0

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q5_K_M

TTFT

Context

131k · 1w ago

Show all run details

Model

deepreinforce-ai/Ornith-1.0-35B

Display name

Ornith-1.0-35B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

yes

Output tok/s

153.0

Prefill tok/s

500.2

Total tok/s

145.9

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

Prefill tokens

Context length

131072

Batch size

32

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q5_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

32

Concurrency

Spec decoding

no

Spec method

Spec model

Spec draft model

Spec tokens

Spec ngram

Spec draft TP

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-35b-Q5_K_M.gguf --parallel 32 --ctx-size 131072 -fa on -ctk q5_0 -ctv q4_1 -b 8192 -ub 4096

Extra flags

--ctk q5_0 --ctv q4_1 --b 8192

Notes

UPDATED: Extracted pure decode/prefill metrics from server logs. GGML_SYCL_DISABLE_DNN=1, -b 8192 -ub 4096. 32 concurrent clients. VRAM: 70C, GPU: 69C, Power: 149.5W.

Reactions

Submitted

Jul 6, 2026, 9:22 AM

Last edited

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q5_K_M

TTFT

Context

131k · 1w ago

Show all run details

Model

Frosty40/Ornith-1.0-35B-B70-Turbo

Display name

Ornith-1.0-35B-B70-Turbo

Base model

Ornith-1.0-35B

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

yes

Output tok/s

145.9

Prefill tok/s

Total tok/s

145.9

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

Prefill tokens

Context length

131072

Batch size

32

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q5_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

32

Concurrency

Spec decoding

no

Spec method

Spec model

Spec draft model

Spec tokens

Spec ngram

Spec draft TP

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-35b-Q5_K_M.gguf --parallel 32 --ctx-size 131072 -fa on -ctk q5_0 -ctv q4_1 -b 8192 -ub 4096

Extra flags

--ctk q5_0 --ctv q4_1 --b 8192

Notes

GGML_SYCL_DISABLE_DNN=1, -b 8192 -ub 4096. 32 concurrent clients. Aggregate throughput for fleet/concurrency usage.

Reactions

Submitted

Jul 6, 2026, 9:04 AM

Last edited

50.3

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q6_K

TTFT

58ms

Context

262k · 2w ago

Show all run details

Model

deepreinforce-ai/Ornith-1.0-9B

Display name

Ornith-1.0-9B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

no

Output tok/s

50.3

Prefill tok/s

553.9

Total tok/s

56.2

TTFT

57.8ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q6_K

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

flash_attn

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-9b-Q6_K.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV. Q6_K weights. 150W power cap. 256K context at 50 t/s — only 15GB VRAM used, could reach 512K+. Highest context headroom of any tested model. Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 64C.

Reactions

Submitted

Jul 1, 2026, 8:42 PM

Last edited

Agents-A1

35B MoE · Qwen

73.2

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q4_K_M

TTFT

77ms

Context

262k · 2w ago

Show all run details

Model

InternScience/Agents-A1

Display name

Agents-A1

Base model

Revision

main

Family

Qwen

Parameters

35B

Active params

MoE

yes

Output tok/s

73.2

Prefill tok/s

416.1

Total tok/s

80.9

TTFT

76.9ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q4_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

flash_attn

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Agents-A1-Q4_K_M.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV (92.65% tail precision). 150W power cap. 256K context at 73 t/s engine. Agent-optimized 35B MoE model. Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 67C. Zero context scaling penalty.

Reactions

Submitted

Jul 1, 2026, 8:41 PM

Last edited

74.3

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q4_K_M

TTFT

73ms

Context

262k · 2w ago

Show all run details

Model

deepreinforce-ai/Ornith-1.0-35B

Display name

Ornith-1.0-35B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

yes

Output tok/s

74.3

Prefill tok/s

440.8

Total tok/s

82.1

TTFT

72.6ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q4_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

flash_attn

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-35b-Q4_K_M.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV (92.65% tail precision). 150W power cap — MoE compute-bound. 256K context at 74 t/s engine — fastest overall. Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 67C. Zero context scaling penalty vs 128K.

Reactions

Submitted

Jul 1, 2026, 8:40 PM

Last edited

Qwen3.6-27B

28B · Qwen

29.7

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q5_K_M

TTFT

312ms

Context

131k · 2w ago

Show all run details

Model

Qwen/Qwen3.6-27B

Display name

Qwen3.6-27B

Base model

Revision

main

Family

Qwen

Parameters

28B

Active params

MoE

no

Output tok/s

29.7

Prefill tok/s

102.4

Total tok/s

32.5

TTFT

312.4ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

flash_attn

Flash attention

yes

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

yes

Spec method

draft-mtp

Spec model

Spec draft model

Spec tokens

4

Spec ngram

Spec draft TP

MTP enabled

yes

MTP draft layers

4

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Qwen3.6-27B-MTP-Q5_K_M.gguf -c 131072 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap --spec-type draft-mtp --spec-draft-n-max 4 --spec-draft-p-min 0.75

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1 --spec-type draft-mtp --spec-draft-n-max 4 --spec-draft-p-min 0.75

Notes

q5_0-q4_1 asymmetric KV. 230W stock power cap — max perf config. MTP-4 speculative decoding (95% draft acceptance). Dense 27B is memory-bandwidth bound, benefits from max power. Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 77C under load.

Reactions

Submitted

Jul 1, 2026, 8:39 PM

Last edited

Qwen3.6-35B-A3B

3B MoE · Qwen

67.0

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q5_K_M

TTFT

69ms

Context

262k · 2w ago

Show all run details

Model

Qwen/Qwen3.6-35B-A3B

Display name

Qwen3.6-35B-A3B

Base model

Revision

main

Family

Qwen

Parameters

36B

Active params

3B

MoE

yes

Output tok/s

67

Prefill tok/s

464.9

Total tok/s

74

TTFT

68.8ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

flash_attn

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Qwen3.6-35B-A3B-UD-Q5_K_M.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV (92.65% tail precision, 38% VRAM savings vs q8_0). 150W power cap — MoE compute-bound, higher power provides negligible benefit. 256K context at 62 t/s engine. Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 65C.

Reactions

Submitted

Jul 1, 2026, 8:38 PM

Last edited

50.3

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q6_K

TTFT

58ms

Context

262k · 2w ago

Show all run details

Model

deepreinforce-ai/Ornith-1.0-9B

Display name

Ornith-1.0-9B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

no

Output tok/s

50.3

Prefill tok/s

553.9

Total tok/s

TTFT

57.8ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q6_K

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-9b-Q6_K.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV cache. Q6_K model weights. 150W power cap. 256K context — only 15GB VRAM used, could reach 512K+. Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 64C under load. Highest context headroom of any tested model.

Reactions

Submitted

Jul 1, 2026, 8:34 PM

Last edited

Agents-A1

35B MoE · Qwen

73.2

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q4_K_M

TTFT

77ms

Context

262k · 2w ago

Show all run details

Model

InternScience/Agents-A1

Display name

Agents-A1

Base model

Revision

main

Family

Qwen

Parameters

35B

Active params

MoE

yes

Output tok/s

73.2

Prefill tok/s

416.1

Total tok/s

TTFT

76.9ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q4_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Agents-A1-Q4_K_M.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV cache (92.65% tail precision, 38% less VRAM than q8_0). 150W power cap — MoE model, compute-bound. 256K context with q5_0-q4_1 KV. Agent-optimized model at massive context window. Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 67C under load. Zero context scaling penalty vs 128K.

Reactions

Submitted

Jul 1, 2026, 8:33 PM

Last edited

74.3

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q4_K_M

TTFT

73ms

Context

262k · 2w ago

Show all run details

Model

deepreinforce-ai/Ornith-1.0-35B

Display name

Ornith-1.0-35B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

yes

Output tok/s

74.3

Prefill tok/s

440.8

Total tok/s

TTFT

72.6ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q4_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-35b-Q4_K_M.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV cache (92.65% tail precision, 38% less VRAM than q8_0). 150W power cap — MoE model is compute-bound, higher power provides negligible benefit. 256K context at 150W with q5_0-q4_1 KV (would need q8_0-q8_0 for same context, costing +38% VRAM). Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 67C under load. Zero context scaling penalty vs 128K.

Reactions

Submitted

Jul 1, 2026, 8:32 PM

Last edited

Qwen3.6-27B

28B · Qwen

26.6

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q5_K_M

TTFT

310ms

Context

205k · 2w ago

Show all run details

Model

Qwen/Qwen3.6-27B

Display name

Qwen3.6-27B

Base model

Revision

main

Family

Qwen

Parameters

28B

Active params

MoE

no

Output tok/s

26.6

Prefill tok/s

103.2

Total tok/s

TTFT

310.0ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

204800

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

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

yes

Spec method

draft-mtp

Spec model

Spec draft model

Spec tokens

4

Spec ngram

Spec draft TP

MTP enabled

yes

MTP draft layers

4

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Qwen3.6-27B-MTP-Q5_K_M.gguf -c 204800 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap --spec-type draft-mtp --spec-draft-n-max 4 --spec-draft-p-min 0.75

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1 --spec-type draft-mtp --spec-draft-n-max 4 --spec-draft-p-min 0.75

Notes

q5_0-q4_1 asymmetric KV cache. Intel oneAPI 2026.0.0 + IntelLLVM 2026.0.0. SYCL backend.

Reactions

Submitted

Jul 1, 2026, 8:30 PM

Last edited

Qwen3.6-35B-A3B

3B MoE · Qwen

67.0

tok/s

Hardware

Intel Arc Pro B70 32GB

Engine

llama.cpp · Q5_K_M

TTFT

69ms

Context

262k · 2w ago

Show all run details

Model

Qwen/Qwen3.6-35B-A3B

Display name

Qwen3.6-35B-A3B

Base model

Revision

main

Family

Qwen

Parameters

36B

Active params

3B

MoE

yes

Output tok/s

67

Prefill tok/s

464.9

Total tok/s

TTFT

68.8ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Qwen3.6-35B-A3B-UD-Q5_K_M.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV cache. Intel oneAPI 2026.0.0 + IntelLLVM 2026.0.0. SYCL backend.

Reactions

Submitted

Jul 1, 2026, 8:28 PM

Last edited

ModelHardwareEnginetok/s outprefilltok/s totalTTFTDepthShare
gemma-4-31B-it

33B · Gemma

Intel Arc Pro B70 32GB
llama.cppQ4_K_M26.6384.8
Show all details for gemma-4-31B-it

Model

google/gemma-4-31B-it

Display name

gemma-4-31B-it

Base model

gemma-4-31B

Revision

main

Family

Gemma

Parameters

33B

Active params

MoE

no

Output tok/s

26.6

Prefill tok/s

384.8

Total tok/s

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q4_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q8_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m gemma-4-31B-it-Q4_K_M.gguf --spec-type draft-mtp --spec-draft-model mtp-gemma-4-31B-it.gguf --spec-draft-n-max 4 -fa on -ctk q8_0 -ctv q4_1 -c 131072 -b 8192 -ub 4096

Extra flags

--spec-type draft-mtp --spec-draft-model mtp-gemma-4-31B-it.gguf --spec-draft-n-max 4 --ctk q8_0 --ctv q4_1 --b 8192

Notes

Gemma-4-31B-it Q4_K_M + MTP-4 @180W best dense decode in sweep. Prefill ~4k. 2026-07-16.

Reactions

Submitted

Jul 16, 2026, 9:49 AM

Last edited

gemma-4-31B-it

33B · Gemma

Intel Arc Pro B70 32GB
llama.cppQ4_K_M24.8361.2
Show all details for gemma-4-31B-it

Model

google/gemma-4-31B-it

Display name

gemma-4-31B-it

Base model

gemma-4-31B

Revision

main

Family

Gemma

Parameters

33B

Active params

MoE

no

Output tok/s

24.8

Prefill tok/s

361.2

Total tok/s

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q4_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q8_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m gemma-4-31B-it-Q4_K_M.gguf --spec-type draft-mtp --spec-draft-model mtp-gemma-4-31B-it.gguf --spec-draft-n-max 4 -fa on -ctk q8_0 -ctv q4_1 -c 131072 -b 8192 -ub 4096

Extra flags

--spec-type draft-mtp --spec-draft-model mtp-gemma-4-31B-it.gguf --spec-draft-n-max 4 --ctk q8_0 --ctv q4_1 --b 8192

Notes

Gemma-4-31B-it Q4_K_M + Unsloth mtp-gemma-4-31B-it draft-mtp n-max 4 @165W. Decode +51% vs base. Prefill ~4k. 2026-07-16.

Reactions

Submitted

Jul 16, 2026, 9:49 AM

Last edited

gemma-4-31B-it

33B · Gemma

Intel Arc Pro B70 32GB
llama.cppQ4_K_M16.4332.9
Show all details for gemma-4-31B-it

Model

google/gemma-4-31B-it

Display name

gemma-4-31B-it

Base model

gemma-4-31B

Revision

main

Family

Gemma

Parameters

33B

Active params

MoE

no

Output tok/s

16.4

Prefill tok/s

332.9

Total tok/s

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q4_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q8_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m gemma-4-31B-it-Q4_K_M.gguf -fa on -ctk q8_0 -ctv q4_1 -c 131072 -b 8192 -ub 4096

Extra flags

--ctk q8_0 --ctv q4_1 --b 8192

Notes

Gemma-4-31B-it Q4_K_M BASE no MTP @150W. Single-stream dense control. Prefill ~4k. 2026-07-16.

Reactions

Submitted

Jul 16, 2026, 9:49 AM

Last edited

Qwen3.5-27B

28B · Qwen

Intel Arc Pro B70 32GB
llama.cppQ5_K_M25.1613.0
Show all details for Qwen3.5-27B

Model

Qwen/Qwen3.5-27B

Display name

Qwen3.5-27B

Base model

Revision

main

Family

Qwen

Parameters

28B

Active params

MoE

no

Output tok/s

25.1

Prefill tok/s

613.0

Total tok/s

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

Prefill tokens

Context length

204800

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q8_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Qwen3.6-27B-MTP-Q5_K_M.gguf --spec-type draft-mtp --spec-draft-n-max 4 -fa on -ctk q8_0 -ctv q4_1 -c 204800 -b 8192 -ub 4096

Extra flags

--spec-type draft-mtp --spec-draft-n-max 4 --ctk q8_0 --ctv q4_1 --b 8192

Notes

Qwen3.6-27B-MTP-Q5_K_M dense + draft-mtp n-max 4. Single-stream. Prefill ~4k. Profile qwen27-mtp-q5-256k-165w @165W. 2026-07-16.

Reactions

Submitted

Jul 16, 2026, 9:49 AM

Last edited

Qwen3.5-35B-A3B

35B · Qwen

Intel Arc Pro B70 32GB
llama.cppQ4_K_XL62.81682.4
Show all details for Qwen3.5-35B-A3B

Model

Qwen/Qwen3.5-35B-A3B

Display name

Qwen3.5-35B-A3B

Base model

Qwen3.5-35B-A3B-Base

Revision

main

Family

Qwen

Parameters

35B

Active params

MoE

no

Output tok/s

62.8

Prefill tok/s

1682.4

Total tok/s

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q4_K_XL

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q8_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Qwen3.6-35B-A3B-UD-Q4_K_XL.gguf -ngl 99 -ncmoe 0 -fa on -ctk q8_0 -ctv q4_1 -c 262144 -b 8192 -ub 4096

Extra flags

--ncmoe 0 --ctk q8_0 --ctv q4_1 --b 8192

Notes

Qwen3.6-35B-A3B UD-Q4_K_XL. Single-stream. Prefill ~4k. Profile qwen35-q4-256k. 2026-07-16.

Reactions

Submitted

Jul 16, 2026, 9:49 AM

Last edited

Qwen3.5-35B-A3B

35B · Qwen

Intel Arc Pro B70 32GB
llama.cppQ5_K_M61.51690.2
Show all details for Qwen3.5-35B-A3B

Model

Qwen/Qwen3.5-35B-A3B

Display name

Qwen3.5-35B-A3B

Base model

Qwen3.5-35B-A3B-Base

Revision

main

Family

Qwen

Parameters

35B

Active params

MoE

no

Output tok/s

61.5

Prefill tok/s

1690.2

Total tok/s

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q8_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Qwen3.6-35B-A3B-UD-Q5_K_M.gguf -ngl 99 -ncmoe 0 -fa on -ctk q8_0 -ctv q4_1 -c 262144 -b 8192 -ub 4096

Extra flags

--ncmoe 0 --ctk q8_0 --ctv q4_1 --b 8192

Notes

Qwen3.6-35B-A3B UD-Q5_K_M GGUF served as active. Single-stream. Prefill ~4k tokens. Profile qwen35-q5-256k. 2026-07-16.

Reactions

Submitted

Jul 16, 2026, 9:49 AM

Last edited

Ornith-1.0-35B

Qwen

Intel Arc Pro B70 32GB
llama.cppQ5_K_M69.31725.9
Show all details for Ornith-1.0-35B

Model

deepreinforce-ai/Ornith-1.0-35B

Display name

Ornith-1.0-35B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

yes

Output tok/s

69.3

Prefill tok/s

1725.9

Total tok/s

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q8_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-35b-Q5_K_M.gguf -ngl 99 -ncmoe 0 -fa on -ctk q8_0 -ctv q4_1 -c 262144 -b 8192 -ub 4096 -dev SYCL0

Extra flags

--ncmoe 0 --ctk q8_0 --ctv q4_1 --b 8192 --dev SYCL0

Notes

Single-stream SYCL llama-server. Decode from generation task; prefill from ~4k prompt timings.prompt_per_second. -b8192 -ub4096 FA on ctk q8_0 ctv q4_1. Profile ornith35-q5-256k. 2026-07-16.

Reactions

Submitted

Jul 16, 2026, 9:49 AM

Last edited

Ornith-1.0-35B

Qwen

Intel Arc Pro B70 32GB
llama.cppQ5_K_M67.61242.367.6
Show all details for Ornith-1.0-35B

Model

deepreinforce-ai/Ornith-1.0-35B

Display name

Ornith-1.0-35B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

yes

Output tok/s

67.6

Prefill tok/s

1242.3

Total tok/s

67.6

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q5_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-35b-Q5_K_M.gguf --parallel 1 --ctx-size 131072 -fa on -ctk q5_0 -ctv q4_1 -b 8192 -ub 4096

Extra flags

--ctk q5_0 --ctv q4_1 --b 8192

Notes

PEAK SINGLE-STREAM PREFILL TEST: Measured using a contiguous 3000-token prompt block without concurrency (batch=1). Uncovers the raw 1,242 tok/s prefill capacity of the B70 without the massive context-switching overhead incurred in fleet concurrency. Hardware capped at optimal 165W/2400MHz.

Reactions

Submitted

Jul 6, 2026, 9:41 AM

Last edited

Ornith-1.0-35B

Qwen

Intel Arc Pro B70 32GB
llama.cppQ5_K_M164.5383.4171.1
Show all details for Ornith-1.0-35B

Model

deepreinforce-ai/Ornith-1.0-35B

Display name

Ornith-1.0-35B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

yes

Output tok/s

164.5

Prefill tok/s

383.4

Total tok/s

171.1

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

Prefill tokens

Context length

131072

Batch size

32

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q5_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

32

Concurrency

Spec decoding

no

Spec method

Spec model

Spec draft model

Spec tokens

Spec ngram

Spec draft TP

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-35b-Q5_K_M.gguf --parallel 32 --ctx-size 131072 -fa on -ctk q5_0 -ctv q4_1 -b 8192 -ub 4096

Extra flags

--ctk q5_0 --ctv q4_1 --b 8192

Notes

POWER/FREQUENCY UNLOCKED TEST: max_freq pushed to 2800 MHz, power1_cap relaxed to 230W. Telemetry logged 196W sustained draw at 73C. Memory bandwidth bottleneck confirmed: +33% power yielded only +8% throughput over the 165W/2400MHz baseline.

Reactions

Submitted

Jul 6, 2026, 9:33 AM

Last edited

Ornith-1.0-35B

Qwen

Intel Arc Pro B70 32GB
llama.cppQ5_K_M153.0500.2145.9
Show all details for Ornith-1.0-35B

Model

deepreinforce-ai/Ornith-1.0-35B

Display name

Ornith-1.0-35B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

yes

Output tok/s

153.0

Prefill tok/s

500.2

Total tok/s

145.9

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

Prefill tokens

Context length

131072

Batch size

32

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q5_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

32

Concurrency

Spec decoding

no

Spec method

Spec model

Spec draft model

Spec tokens

Spec ngram

Spec draft TP

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-35b-Q5_K_M.gguf --parallel 32 --ctx-size 131072 -fa on -ctk q5_0 -ctv q4_1 -b 8192 -ub 4096

Extra flags

--ctk q5_0 --ctv q4_1 --b 8192

Notes

UPDATED: Extracted pure decode/prefill metrics from server logs. GGML_SYCL_DISABLE_DNN=1, -b 8192 -ub 4096. 32 concurrent clients. VRAM: 70C, GPU: 69C, Power: 149.5W.

Reactions

Submitted

Jul 6, 2026, 9:22 AM

Last edited

Ornith-1.0-35B-B70-Turbo

Qwen

Intel Arc Pro B70 32GB
llama.cppQ5_K_M145.9145.9
Show all details for Ornith-1.0-35B-B70-Turbo

Model

Frosty40/Ornith-1.0-35B-B70-Turbo

Display name

Ornith-1.0-35B-B70-Turbo

Base model

Ornith-1.0-35B

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

yes

Output tok/s

145.9

Prefill tok/s

Total tok/s

145.9

TTFT

Peak VRAM

Power draw

Hardware cost

Prompt tokens

0

Output tokens

0

Prefill tokens

Context length

131072

Batch size

32

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9853 SYCL

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

Split mode

KV cache dtype

q5_0/q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

Chunked prefill

Prefill chunk

4096

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

32

Concurrency

Spec decoding

no

Spec method

Spec model

Spec draft model

Spec tokens

Spec ngram

Spec draft TP

MTP enabled

no

MTP draft layers

Temperature

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-35b-Q5_K_M.gguf --parallel 32 --ctx-size 131072 -fa on -ctk q5_0 -ctv q4_1 -b 8192 -ub 4096

Extra flags

--ctk q5_0 --ctv q4_1 --b 8192

Notes

GGML_SYCL_DISABLE_DNN=1, -b 8192 -ub 4096. 32 concurrent clients. Aggregate throughput for fleet/concurrency usage.

Reactions

Submitted

Jul 6, 2026, 9:04 AM

Last edited

Ornith-1.0-9B

Qwen

Intel Arc Pro B70 32GB
llama.cppQ6_K50.3553.956.258ms
Show all details for Ornith-1.0-9B

Model

deepreinforce-ai/Ornith-1.0-9B

Display name

Ornith-1.0-9B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

no

Output tok/s

50.3

Prefill tok/s

553.9

Total tok/s

56.2

TTFT

57.8ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q6_K

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

flash_attn

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-9b-Q6_K.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV. Q6_K weights. 150W power cap. 256K context at 50 t/s — only 15GB VRAM used, could reach 512K+. Highest context headroom of any tested model. Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 64C.

Reactions

Submitted

Jul 1, 2026, 8:42 PM

Last edited

Agents-A1

35B MoE · Qwen

Intel Arc Pro B70 32GB
llama.cppQ4_K_M73.2416.180.977ms
Show all details for Agents-A1

Model

InternScience/Agents-A1

Display name

Agents-A1

Base model

Revision

main

Family

Qwen

Parameters

35B

Active params

MoE

yes

Output tok/s

73.2

Prefill tok/s

416.1

Total tok/s

80.9

TTFT

76.9ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q4_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

flash_attn

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Agents-A1-Q4_K_M.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV (92.65% tail precision). 150W power cap. 256K context at 73 t/s engine. Agent-optimized 35B MoE model. Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 67C. Zero context scaling penalty.

Reactions

Submitted

Jul 1, 2026, 8:41 PM

Last edited

Ornith-1.0-35B

Qwen

Intel Arc Pro B70 32GB
llama.cppQ4_K_M74.3440.882.173ms
Show all details for Ornith-1.0-35B

Model

deepreinforce-ai/Ornith-1.0-35B

Display name

Ornith-1.0-35B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

yes

Output tok/s

74.3

Prefill tok/s

440.8

Total tok/s

82.1

TTFT

72.6ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q4_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

flash_attn

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-35b-Q4_K_M.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV (92.65% tail precision). 150W power cap — MoE compute-bound. 256K context at 74 t/s engine — fastest overall. Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 67C. Zero context scaling penalty vs 128K.

Reactions

Submitted

Jul 1, 2026, 8:40 PM

Last edited

Qwen3.6-27B

28B · Qwen

Intel Arc Pro B70 32GB
llama.cppQ5_K_M29.7102.432.5312ms
Show all details for Qwen3.6-27B

Model

Qwen/Qwen3.6-27B

Display name

Qwen3.6-27B

Base model

Revision

main

Family

Qwen

Parameters

28B

Active params

MoE

no

Output tok/s

29.7

Prefill tok/s

102.4

Total tok/s

32.5

TTFT

312.4ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

flash_attn

Flash attention

yes

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

yes

Spec method

draft-mtp

Spec model

Spec draft model

Spec tokens

4

Spec ngram

Spec draft TP

MTP enabled

yes

MTP draft layers

4

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Qwen3.6-27B-MTP-Q5_K_M.gguf -c 131072 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap --spec-type draft-mtp --spec-draft-n-max 4 --spec-draft-p-min 0.75

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1 --spec-type draft-mtp --spec-draft-n-max 4 --spec-draft-p-min 0.75

Notes

q5_0-q4_1 asymmetric KV. 230W stock power cap — max perf config. MTP-4 speculative decoding (95% draft acceptance). Dense 27B is memory-bandwidth bound, benefits from max power. Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 77C under load.

Reactions

Submitted

Jul 1, 2026, 8:39 PM

Last edited

Qwen3.6-35B-A3B

3B MoE · Qwen

Intel Arc Pro B70 32GB
llama.cppQ5_K_M67.0464.974.069ms
Show all details for Qwen3.6-35B-A3B

Model

Qwen/Qwen3.6-35B-A3B

Display name

Qwen3.6-35B-A3B

Base model

Revision

main

Family

Qwen

Parameters

36B

Active params

3B

MoE

yes

Output tok/s

67

Prefill tok/s

464.9

Total tok/s

74

TTFT

68.8ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

flash_attn

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Qwen3.6-35B-A3B-UD-Q5_K_M.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV (92.65% tail precision, 38% VRAM savings vs q8_0). 150W power cap — MoE compute-bound, higher power provides negligible benefit. 256K context at 62 t/s engine. Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 65C.

Reactions

Submitted

Jul 1, 2026, 8:38 PM

Last edited

Ornith-1.0-9B

Qwen

Intel Arc Pro B70 32GB
llama.cppQ6_K50.3553.958ms
Show all details for Ornith-1.0-9B

Model

deepreinforce-ai/Ornith-1.0-9B

Display name

Ornith-1.0-9B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

no

Output tok/s

50.3

Prefill tok/s

553.9

Total tok/s

TTFT

57.8ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q6_K

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-9b-Q6_K.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV cache. Q6_K model weights. 150W power cap. 256K context — only 15GB VRAM used, could reach 512K+. Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 64C under load. Highest context headroom of any tested model.

Reactions

Submitted

Jul 1, 2026, 8:34 PM

Last edited

Agents-A1

35B MoE · Qwen

Intel Arc Pro B70 32GB
llama.cppQ4_K_M73.2416.177ms
Show all details for Agents-A1

Model

InternScience/Agents-A1

Display name

Agents-A1

Base model

Revision

main

Family

Qwen

Parameters

35B

Active params

MoE

yes

Output tok/s

73.2

Prefill tok/s

416.1

Total tok/s

TTFT

76.9ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q4_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Agents-A1-Q4_K_M.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV cache (92.65% tail precision, 38% less VRAM than q8_0). 150W power cap — MoE model, compute-bound. 256K context with q5_0-q4_1 KV. Agent-optimized model at massive context window. Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 67C under load. Zero context scaling penalty vs 128K.

Reactions

Submitted

Jul 1, 2026, 8:33 PM

Last edited

Ornith-1.0-35B

Qwen

Intel Arc Pro B70 32GB
llama.cppQ4_K_M74.3440.873ms
Show all details for Ornith-1.0-35B

Model

deepreinforce-ai/Ornith-1.0-35B

Display name

Ornith-1.0-35B

Base model

Revision

main

Family

Qwen

Parameters

0B

Active params

MoE

yes

Output tok/s

74.3

Prefill tok/s

440.8

Total tok/s

TTFT

72.6ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q4_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m ornith-1.0-35b-Q4_K_M.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV cache (92.65% tail precision, 38% less VRAM than q8_0). 150W power cap — MoE model is compute-bound, higher power provides negligible benefit. 256K context at 150W with q5_0-q4_1 KV (would need q8_0-q8_0 for same context, costing +38% VRAM). Intel Arc Pro B70 32GB. llama.cpp SYCL b9851. oneAPI 2026.0.0. GPU temp: 67C under load. Zero context scaling penalty vs 128K.

Reactions

Submitted

Jul 1, 2026, 8:32 PM

Last edited

Qwen3.6-27B

28B · Qwen

Intel Arc Pro B70 32GB
llama.cppQ5_K_M26.6103.2310ms
Show all details for Qwen3.6-27B

Model

Qwen/Qwen3.6-27B

Display name

Qwen3.6-27B

Base model

Revision

main

Family

Qwen

Parameters

28B

Active params

MoE

no

Output tok/s

26.6

Prefill tok/s

103.2

Total tok/s

TTFT

310.0ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

204800

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

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

yes

Spec method

draft-mtp

Spec model

Spec draft model

Spec tokens

4

Spec ngram

Spec draft TP

MTP enabled

yes

MTP draft layers

4

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Qwen3.6-27B-MTP-Q5_K_M.gguf -c 204800 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap --spec-type draft-mtp --spec-draft-n-max 4 --spec-draft-p-min 0.75

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1 --spec-type draft-mtp --spec-draft-n-max 4 --spec-draft-p-min 0.75

Notes

q5_0-q4_1 asymmetric KV cache. Intel oneAPI 2026.0.0 + IntelLLVM 2026.0.0. SYCL backend.

Reactions

Submitted

Jul 1, 2026, 8:30 PM

Last edited

Qwen3.6-35B-A3B

3B MoE · Qwen

Intel Arc Pro B70 32GB
llama.cppQ5_K_M67.0464.969ms
Show all details for Qwen3.6-35B-A3B

Model

Qwen/Qwen3.6-35B-A3B

Display name

Qwen3.6-35B-A3B

Base model

Revision

main

Family

Qwen

Parameters

36B

Active params

3B

MoE

yes

Output tok/s

67

Prefill tok/s

464.9

Total tok/s

TTFT

68.8ms

Peak VRAM

Power draw

Hardware cost

Prompt tokens

32

Output tokens

256

Prefill tokens

Context length

262144

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 7840HS w/ Radeon 780M Graphics

RAM

25.8GB

OS

Windows 11 Pro 10.0.26100 build 26100

Power

230W

Engine

llama.cpp

Engine version

b9851 (0eca4d490)

Quantization

Q5_K_M

Backend

xpu

Tensor parallel

Pipeline parallel

GPU layers

99

Split mode

KV cache dtype

q5_0-q4_1

KV cache size

Prefix caching

Attention backend

Flash attention

yes

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

MTP enabled

no

MTP draft layers

Temperature

8

Top P

Top K

Min P

Repeat penalty

Mirostat

Command

llama-server -m Qwen3.6-35B-A3B-UD-Q5_K_M.gguf -c 262144 -ngl 99 -ncmoe 0 -fa on -ctk q5_0 -ctv q4_1 -t 8 --no-mmap

Extra flags

--ncmoe 0 --ctk q5_0 --ctv q4_1

Notes

q5_0-q4_1 asymmetric KV cache. Intel oneAPI 2026.0.0 + IntelLLVM 2026.0.0. SYCL backend.

Reactions

Submitted

Jul 1, 2026, 8:28 PM

Last edited