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Speed test matrix

granite-4.2-30b-nvfp4 on RTX 3090 24GB

vllm · 0.32.0 · NVFP44 contexts (0–48K) × 8 concurrency levels (1–128) · prefill at 8K, 16K, 32K, 48K
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
NVFP4
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: int4_per_token_head
# 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 ibm-granite/granite-4.2-30b-nvfp4 --max-model-len 57344 --gpu-memory-utilization 0.94 --max-num-seqs 128 --enable-prefix-caching --trust-remote-code --kv-cache-dtype int4_per_token_head --attention-backend TRITON_ATTN

Prefill

prompt tok/s by context length
8K context1,3656,037 ms TTFT
16K context1,06515,323 ms TTFT
32K context746.043,503 ms TTFT
48K context574.084,779 ms TTFT

Sustained decode

total tok/s · rows are context length, columns are simultaneous requests
Context1248163264128
040.375 ms TTFT79.577 ms TTFT152.761 ms TTFTOver capacityOver capacityOver capacityOver capacityOver capacity
16K29.6142 ms TTFT54.5222 ms TTFTOver capacityOver capacityOver capacityOver capacityOver capacityOver capacity
32K23.3259 ms TTFTOver capacityOver capacityOver capacityOver capacityOver capacityOver capacityOver capacity
48K19.3Requests queued426 ms TTFTOver capacityOver capacityOver capacityOver capacityOver capacityOver capacityOver capacity

Requests queued: the server could not run all requests at once, so some waited in a queue. 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
Prefill8K1Valid1,365.0—6,037 ms——1——
Prefill16K1Valid1,065.0—15,323 ms——1——
Prefill32K1Valid746.0—43,503 ms——1——
Prefill48K1Valid574.0—84,779 ms——1——
Sustained decode01Valid40.340.575 ms24.7 ms1.001,21030.0 s
Sustained decode02Valid79.539.977 ms25.1 ms2.002,38430.0 s
Sustained decode04Valid152.738.561 ms26.0 ms4.004,58030.0 s
Sustained decode08Over capacity————————
Sustained decode016Over capacity————————
Sustained decode032Over capacity————————
Sustained decode064Over capacity————————
Sustained decode0128Over capacity————————
Sustained decode16K1Valid29.629.6142 ms33.8 ms1.0088730.0 s
Sustained decode16K2Valid54.527.2222 ms36.7 ms2.001,63430.0 s
Sustained decode16K4Over capacity————————
Sustained decode16K8Over capacity————————
Sustained decode16K16Over capacity————————
Sustained decode16K32Over capacity————————
Sustained decode16K64Over capacity————————
Sustained decode16K128Over capacity————————
Sustained decode32K1Valid23.323.3259 ms42.8 ms1.0069930.0 s
Sustained decode32K2Over capacity————————
Sustained decode32K4Over capacity————————
Sustained decode32K8Over capacity————————
Sustained decode32K16Over capacity————————
Sustained decode32K32Over capacity————————
Sustained decode32K64Over capacity————————
Sustained decode32K128Over capacity————————
Sustained decode48K1Requests queued19.319.3426 ms51.8 ms1.0057830.0 s
Sustained decode48K2Over capacity————————
Sustained decode48K4Over capacity————————
Sustained decode48K8Over capacity————————
Sustained decode48K16Over capacity————————
Sustained decode48K32Over capacity————————
Sustained decode48K64Over capacity————————
Sustained decode48K128Over capacity————————

Requests queued: the server could not run all requests at once, so some waited in a queue. Over capacity: not run because this many requests at this context would exceed the server's KV cache.