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Speed test matrix

LFM2.5-350M on RTX PRO 6000 Blackwell Server Edition 96GB

sglang · 0.5.6.post3.dev9265+g05c584c44 · BF165 contexts (8K–120K) × 8 concurrency levels (1–128) · prefill at 8K, 16K, 32K, 64K, 120K, 125K
by @keennaylmx dev importMeasured

Hardware

Type
Discrete GPU
GPU
RTX PRO 6000 Blackwell Server Edition
VRAM
96 GB
OS
linux

Engine

Engine
sglang
Version
0.5.6.post3.dev9265+g05c584c44
Quantization
BF16
Backend
cuda
Build
cuda-13.2
Commit
05c584c44fb0

Run

Served model
lfm
Revision
main
Decode test
Fixed duration
Prefill mode
Measured during decode warm-up
Time per measurement
30 s
Max output
4,096 tokens

Launch command

env SGLANG_ALLOW_OVERWRITE_LONGER_CONTEXT_LEN=1 "$HOME/env_rtxpro6k-liquidai-sglang/bin/sglang" serve --model-path LiquidAI/LFM2.5-350M --served-model-name lfm --trust-remote-code --tp 1 --tool-call-parser lfm2 --context-length 128000 --mem-fraction-static 0.79 --enable-metrics --host 0.0.0.0 --port 8000 --api-key <redacted>

Prefill

prompt tok/s by context length
8K context151.9K54 ms TTFT
16K context175.7K92 ms TTFT
32K context176.3K183 ms TTFT
64K context147.3K438 ms TTFT
120K context78.8K1,532 ms TTFT
125K context110.4K1,140 ms TTFT

Sustained decode

total tok/s · rows are context length, columns are simultaneous requests
Context1248163264128
8KLoopedLoopedLoopedLoopedLoopedLoopedLoopedLooped
16KLoopedLoopedLoopedLoopedLoopedLoopedLoopedLooped
32KLoopedLoopedLoopedLoopedLoopedLoopedLoopedOver capacity
64KLoopedLooped1,726.7314 ms TTFTLoopedLoopedLoopedOver capacityOver capacity
120K388.0267 ms TTFT717.8313 ms TTFT1,393.5474 ms TTFT2,199.9574 ms TTFT2,956.51,616 ms TTFTOver capacityOver capacityOver capacity

Looped: the model kept repeating the same text, so the benchmark discarded this measurement. Over capacity: not run because this many requests at this context would exceed the server's KV cache.

TTFT is measured after the benchmark warms the server's prompt cache, so it mostly excludes prefill.

All measurements

Latencies are medians. Total tok/s is output across all simultaneous requests.
PhaseContextRequests at onceStatusTotal tok/sPer request tok/sTTFTTime between tokensAverage active requestsCompleted requestsOutput tokensMeasured for
Prefill8K1Valid151.9K—54 ms——1——
Prefill16K1Valid175.7K—92 ms——1——
Prefill32K1Valid176.3K—183 ms——1——
Prefill64K1Valid147.3K—438 ms——1——
Prefill120K1Valid78.8K—1,532 ms——1——
Prefill125K1Valid110.4K—1,140 ms——1——
Sustained decode8K1Looped—————00—
Sustained decode8K2Looped—————00—
Sustained decode8K4Looped—————00—
Sustained decode8K8Looped—————00—
Sustained decode8K16Looped—————00—
Sustained decode8K32Looped—————00—
Sustained decode8K64Looped—————00—
Sustained decode8K128Looped—————00—
Sustained decode16K1Looped—————00—
Sustained decode16K2Looped—————00—
Sustained decode16K4Looped—————00—
Sustained decode16K8Looped—————00—
Sustained decode16K16Looped—————00—
Sustained decode16K32Looped—————00—
Sustained decode16K64Looped—————00—
Sustained decode16K128Looped—————00—
Sustained decode32K1Looped—————00—
Sustained decode32K2Looped—————00—
Sustained decode32K4Looped—————00—
Sustained decode32K8Looped—————00—
Sustained decode32K16Looped—————00—
Sustained decode32K32Looped—————00—
Sustained decode32K64Looped—————00—
Sustained decode32K128Over capacity————————
Sustained decode64K1Looped—————00—
Sustained decode64K2Looped—————00—
Sustained decode64K4Valid1,726.7446.1314 ms2.2 ms3.81251,80130.0 s
Sustained decode64K8Looped—————00—
Sustained decode64K16Looped—————00—
Sustained decode64K32Looped—————00—
Sustained decode64K64Over capacity————————
Sustained decode64K128Over capacity————————
Sustained decode120K1Valid388.0399.5267 ms2.5 ms0.9311,64130.0 s
Sustained decode120K2Valid717.8370.6313 ms2.7 ms1.9621,53230.0 s
Sustained decode120K4Valid1,393.5359.9474 ms2.8 ms3.9841,80630.0 s
Sustained decode120K8Valid2,199.9284.5574 ms3.5 ms7.81665,99630.0 s
Sustained decode120K16Valid2,956.5190.41,616 ms5.3 ms15.81688,68830.0 s
Sustained decode120K32Over capacity————————
Sustained decode120K64Over capacity————————
Sustained decode120K128Over capacity————————

Looped: the model kept repeating the same text, so the benchmark discarded this measurement. Over capacity: not run because this many requests at this context would exceed the server's KV cache.