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Speed test matrix

Qwen3.8-27B-INT4 on RTX 3090 24GB

vllm · 0.32.0 · INT4 W4A16 g1283 contexts (0–24K) × 8 concurrency levels (1–128) · prefill at 8K, 16K, 24K
by @Sandbergllm-inference-bench v0.8.0Measured Edited

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
INT4 W4A16 g128
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
# 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 RedHatAI/Qwen3.8-27B-INT4 --max-model-len 32768 --gpu-memory-utilization 0.94 --max-num-seqs 54 --enable-prefix-caching --trust-remote-code --language-model-only --max-cudagraph-capture-size 16

Prefill

prompt tok/s by context length
8K context2,1793,779 ms TTFT
16K context2,0887,790 ms TTFT
24K context2,01212,075 ms TTFT

Sustained decode

total tok/s · rows are context length, columns are simultaneous requests
Context1248163264128
048.281 ms TTFT89.2414 ms TTFT171.1266 ms TTFTOver capacityOver capacityOver capacityOver capacityOver capacity
16K45.3400 ms TTFTOver capacityOver capacityOver capacityOver capacityOver capacityOver capacityOver capacity
24K44.1515 ms TTFTOver capacityOver capacityOver capacityOver capacityOver capacityOver capacityOver capacity

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
Prefill8K1Valid2,179.0—3,779 ms——1——
Prefill16K1Valid2,088.0—7,790 ms——1——
Prefill24K1Valid2,012.0—12,075 ms——1——
Sustained decode01Valid48.248.281 ms20.8 ms1.001,44430.0 s
Sustained decode02Valid89.244.6414 ms22.4 ms2.002,67430.0 s
Sustained decode04Valid171.142.9266 ms23.3 ms4.005,13230.0 s
Sustained decode08Over capacity————————
Sustained decode016Over capacity————————
Sustained decode032Over capacity————————
Sustained decode064Over capacity————————
Sustained decode0128Over capacity————————
Sustained decode16K1Valid45.345.3400 ms22.1 ms1.001,35830.0 s
Sustained decode16K2Over capacity————————
Sustained decode16K4Over capacity————————
Sustained decode16K8Over capacity————————
Sustained decode16K16Over capacity————————
Sustained decode16K32Over capacity————————
Sustained decode16K64Over capacity————————
Sustained decode16K128Over capacity————————
Sustained decode24K1Valid44.144.1515 ms22.7 ms1.001,32230.0 s
Sustained decode24K2Over capacity————————
Sustained decode24K4Over capacity————————
Sustained decode24K8Over capacity————————
Sustained decode24K16Over capacity————————
Sustained decode24K32Over capacity————————
Sustained decode24K64Over capacity————————
Sustained decode24K128Over capacity————————

Over capacity: not run because this many requests at this context would exceed the server's KV cache.