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Speed test matrix

Qwen3-Coder-30B-A3B-Instruct-AWQ-4bit on RTX 3090 24GB

vllm · 0.32.0 · AWQ 4-bit4 contexts (0–64K) × 8 concurrency levels (1–128) · prefill at 8K, 16K, 32K, 64K
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 4-bit
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 cyankiwi/Qwen3-Coder-30B-A3B-Instruct-AWQ-4bit --max-model-len 73728 --gpu-memory-utilization 0.94 --max-num-seqs 128 --enable-prefix-caching --trust-remote-code --kv-cache-dtype fp8

Prefill

prompt tok/s by context length
8K context9,630857 ms TTFT
16K context7,3742,217 ms TTFT
32K context5,1676,299 ms TTFT
64K context3,13320,729 ms TTFT

Sustained decode

total tok/s · rows are context length, columns are simultaneous requests
Context1248163264128
0179.626 ms TTFT298.229 ms TTFT488.834 ms TTFT780.842 ms TTFTOver capacityOver capacityOver capacityOver capacity
16K153.653 ms TTFT261.475 ms TTFTOver capacityOver capacityOver capacityOver capacityOver capacityOver capacity
32KLoopedOver capacityOver capacityOver capacityOver capacityOver capacityOver capacityOver capacity
64K108.2169 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
Prefill8K1Valid9,630.0—857 ms——1——
Prefill16K1Valid7,374.0—2,217 ms——1——
Prefill32K1Valid5,167.0—6,299 ms——1——
Prefill64K1Valid3,133.0—20,729 ms——1——
Sustained decode01Valid179.6180.426 ms5.5 ms1.005,38730.0 s
Sustained decode02Valid298.2150.629 ms6.6 ms2.008,94630.0 s
Sustained decode04Valid488.8123.934 ms8.1 ms4.0014,66330.0 s
Sustained decode08Valid780.899.742 ms10.0 ms8.0023,42430.0 s
Sustained decode016Over capacity————————
Sustained decode032Over capacity————————
Sustained decode064Over capacity————————
Sustained decode0128Over capacity————————
Sustained decode16K1Valid153.6153.853 ms6.5 ms1.004,60830.0 s
Sustained decode16K2Valid261.4131.175 ms7.6 ms2.007,84030.0 s
Sustained decode16K4Over capacity————————
Sustained decode16K8Over capacity————————
Sustained decode16K16Over capacity————————
Sustained decode16K32Over capacity————————
Sustained decode16K64Over capacity————————
Sustained decode16K128Over capacity————————
Sustained decode32K1Looped—————00—
Sustained decode32K2Over capacity————————
Sustained decode32K4Over capacity————————
Sustained decode32K8Over capacity————————
Sustained decode32K16Over capacity————————
Sustained decode32K32Over capacity————————
Sustained decode32K64Over capacity————————
Sustained decode32K128Over capacity————————
Sustained decode64K1Valid108.2108.4169 ms9.2 ms1.003,24530.0 s
Sustained decode64K2Over capacity————————
Sustained decode64K4Over capacity————————
Sustained decode64K8Over capacity————————
Sustained decode64K16Over capacity————————
Sustained decode64K32Over capacity————————
Sustained decode64K64Over capacity————————
Sustained decode64K128Over 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.