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gemma-4-12B-it · Q4_K_M

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NVIDIA RTX 409024GBvLLM 0.7.3L0 Self-reported

This page aggregates 1 real-world runs of gemma-4-12B-it (Q4_K_M) on NVIDIA RTX 4090 with vLLM, contributed by 1 independent source platforms; metrics are averages of published measurements.

117.4 tok/s

Decode

Decode speed

880.5 tok/s

Prefill

Prefill speed

0.11 s

TTFT

Time to first token

7.8 GB

VRAM

VRAM usage

L0 Self-reported

1

Measured runs

1

Independent sources

Other

Source platforms

Today

Last verified

Performance

  1. vLLM · Q8_0 Decode 65.9 · Prefill 494.3 ·
  2. vLLM · Q5_K_M Decode 96.3 · Prefill 722.3 ·
  3. vLLM · Q4_K_M (current)Decode 117.4 · Prefill 880.5 ·
  4. llama.cpp · Q8_0 Decode 60.5 · Prefill 453.8 ·
  5. llama.cpp · Q5_K_M Decode 88.3 · Prefill 662.3 ·
  6. llama.cpp · Q4_K_M Decode 107.7 · Prefill 807.8 ·

Core figures

Decode (avg)
117.4 tok/s
Prefill (avg)
880.5 tok/s
TTFT (avg)
0.11 s
VRAM (avg)
7.8 GB
MTP acceptance rate
—
TTFB
— GB
Power draw
— W

Configuration

Member-level fields are taken from the most recent run

Model
gemma-4-12B-it
Quantization
Q4_K_M
Framework
vLLM
Version
0.7.3
Context length
4096 tokens
Batch size
512
GPU layers
99
Flash Attention
On

Hardware

Nominal and measured figures are shown side by side; whether it runs is the reader's call

GPU
NVIDIA RTX 4090
Nominal VRAM
24 GB
Measured VRAM (avg)
7.8 GB
OS
Linux
Driver
570.65
CUDA
12.6

Sources & evidence

1 measured records in total, each traceable to its original source

  1. L0 Self-reportedOtherOriginal link Verified on 2026-10-06

    0.7.3 · Linux · CUDA 12.6 · 4096 ctx

    117.4 tok/s

    Decode

    880.5 tok/s

    Prefill

    0.11 s

    TTFT

    7.8 GB

    VRAM

    —

    MTP

    — W

    Power draw

    L0 理论估算（add-1000-records-batch3）