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Speed test matrix

Fara1.5-27B-AWQ-W4A16 on RTX 3090 24GB

vllm · 0.32.0 · AWQ W4A164 contexts (0–56K) × 8 concurrency levels (1–128) · prefill at 8K, 16K, 32K, 56K
by @Sandbergllm-inference-bench v0.8.0Measured

Hardware

Type
Discrete GPU
GPU
RTX 3090
VRAM
24 GB
CPU
Intel Core i7-9700K (8C)
RAM
32 GB
OS
Ubuntu 24.04.5

Engine

Engine
vllm
Version
0.32.0
Quantization
AWQ W4A16
Backend
cuda
Build
vllm/vllm-openai:v0.32.0-x86_64

Run

Served model
bench
Revision
main
Decode test
Fixed duration
Prefill mode
Measured during decode warm-up
Time per measurement
30 s
Max output
8,192 tokens

Launch command

# Untuned out-of-the-box baseline. Spec decode: none. KV cache: fp8
# 1x RTX 3090 24GB (Zagitta/gpu-unlock), 420 W limit, PCIe Gen3 x16 | Intel Core i7-9700K 8C | 32 GB DDR4 | Ubuntu 24.04.5, NVIDIA driver 580.178.04
vllm serve Sohailhosseini/Fara1.5-27B-AWQ-W4A16 --max-model-len 65536 --gpu-memory-utilization 0.94 --max-num-seqs 51 --enable-prefix-caching --trust-remote-code --language-model-only --kv-cache-dtype fp8 --max-cudagraph-capture-size 16

Prefill

prompt tok/s by context length
8K context2,1443,819 ms TTFT
16K context2,0248,013 ms TTFT
32K context1,86317,336 ms TTFT
56K context1,66233,928 ms TTFT

Sustained decode

total tok/s · rows are context length, columns are simultaneous requests
Context1248163264128
047.983 ms TTFT89.098 ms TTFT171.3227 ms TTFT332.3368 ms TTFTOver capacityOver capacityOver capacityOver capacity
16KLooped85.8519 ms TTFTOver capacityOver capacityOver capacityOver capacityOver capacityOver capacity
32K45.1665 ms TTFTOver capacityOver capacityOver capacityOver capacityOver capacityOver capacityOver capacity
56K43.41,242 ms TTFTOver capacityOver capacityOver capacityOver capacityOver 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
Prefill8K1Valid2,144.0—3,819 ms——1——
Prefill16K1Valid2,024.0—8,013 ms——1——
Prefill32K1Valid1,863.0—17,336 ms——1——
Prefill56K1Valid1,662.0—33,928 ms——1——
Sustained decode01Valid47.948.083 ms20.9 ms1.001,43730.0 s
Sustained decode02Valid89.044.598 ms22.5 ms2.002,66830.0 s
Sustained decode04Valid171.342.9227 ms23.3 ms4.005,14030.0 s
Sustained decode08Valid332.341.6368 ms24.0 ms8.009,96930.0 s
Sustained decode016Over capacity————————
Sustained decode032Over capacity————————
Sustained decode064Over capacity————————
Sustained decode0128Over capacity————————
Sustained decode16K1Looped—————00—
Sustained decode16K2Valid85.842.7519 ms23.4 ms2.002,57230.0 s
Sustained decode16K4Over capacity————————
Sustained decode16K8Over capacity————————
Sustained decode16K16Over capacity————————
Sustained decode16K32Over capacity————————
Sustained decode16K64Over capacity————————
Sustained decode16K128Over capacity————————
Sustained decode32K1Valid45.145.1665 ms22.2 ms1.001,35330.0 s
Sustained decode32K2Over capacity————————
Sustained decode32K4Over capacity————————
Sustained decode32K8Over capacity————————
Sustained decode32K16Over capacity————————
Sustained decode32K32Over capacity————————
Sustained decode32K64Over capacity————————
Sustained decode32K128Over capacity————————
Sustained decode56K1Valid43.443.41,242 ms23.1 ms1.001,30130.0 s
Sustained decode56K2Over capacity————————
Sustained decode56K4Over capacity————————
Sustained decode56K8Over capacity————————
Sustained decode56K16Over capacity————————
Sustained decode56K32Over capacity————————
Sustained decode56K64Over capacity————————
Sustained decode56K128Over 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.