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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
AMD Ryzen 9 7900X (12C)
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), 350 W limit (VBIOS max), PCIe Gen4 x16 | AMD Ryzen 9 7900X 12C | 32 GB DDR5 | Ubuntu 24.04.5, NVIDIA driver 595.99.02
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 context8,583961 ms TTFT
16K context6,7002,440 ms TTFT
32K context4,5237,196 ms TTFT
64K context2,71123,950 ms TTFT

Sustained decode

total tok/s · rows are context length, columns are simultaneous requests
Context1248163264128
0175.027 ms TTFT290.531 ms TTFT472.731 ms TTFT753.138 ms TTFTOver capacityOver capacityOver capacityOver capacity
16KLoopedLoopedOver capacityOver capacityOver capacityOver capacityOver capacityOver capacity
32K130.161 ms TTFTOver capacityOver capacityOver capacityOver capacityOver capacityOver capacityOver capacity
64K104.5113 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
Prefill8K1Valid8,583.0—961 ms——1——
Prefill16K1Valid6,700.0—2,440 ms——1——
Prefill32K1Valid4,523.0—7,196 ms——1——
Prefill64K1Valid2,711.0—23,950 ms——1——
Sustained decode01Valid175.0176.127 ms5.7 ms1.005,24930.0 s
Sustained decode02Valid290.5146.631 ms6.8 ms2.008,71630.0 s
Sustained decode04Valid472.7120.031 ms8.3 ms4.0014,18030.0 s
Sustained decode08Valid753.196.238 ms10.4 ms8.0022,59230.0 s
Sustained decode016Over capacity————————
Sustained decode032Over capacity————————
Sustained decode064Over capacity————————
Sustained decode0128Over capacity————————
Sustained decode16K1Looped—————00—
Sustained decode16K2Looped—————00—
Sustained decode16K4Over capacity————————
Sustained decode16K8Over capacity————————
Sustained decode16K16Over capacity————————
Sustained decode16K32Over capacity————————
Sustained decode16K64Over capacity————————
Sustained decode16K128Over capacity————————
Sustained decode32K1Valid130.1130.361 ms7.7 ms1.003,90230.0 s
Sustained decode32K2Over capacity————————
Sustained decode32K4Over capacity————————
Sustained decode32K8Over capacity————————
Sustained decode32K16Over capacity————————
Sustained decode32K32Over capacity————————
Sustained decode32K64Over capacity————————
Sustained decode32K128Over capacity————————
Sustained decode64K1Valid104.5104.6113 ms9.6 ms1.003,13530.0 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.