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gemma-4-E4B-it · IQ3_S

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Apple M2 ProvLLM v0.24L2 Cross-framework verified

This page aggregates 1 real-world runs of gemma-4-E4B-it (IQ3_S) on Apple M2 Pro with vLLM, contributed by 1 independent source platforms; metrics are averages of published measurements.

120.89 tok/s

Decode

Decode speed

462.7 tok/s

Prefill

Prefill speed

1.07 s

TTFT

Time to first token

7.64 GB

VRAM

VRAM usage

L2 Cross-framework verified

1

Measured runs

1

Independent sources

Other

Source platforms

2 days ago

Last verified

Performance

  1. vLLM · FP16 Decode 45.65 · Prefill 229.99 ·
  2. vLLM · IQ3_S (current)Decode 120.89 · Prefill 462.7 ·
  3. Ollama · Q3_K_S Decode 106.08 · Prefill 378.66 ·

Core figures

Decode (avg)
120.89 tok/s
Prefill (avg)
462.7 tok/s
TTFT (avg)
1.07 s
VRAM (avg)
7.64 GB
MTP acceptance rate
—
TTFB
0.97 GB
Power draw
38.7 W

Configuration

Member-level fields are taken from the most recent run

Model
gemma-4-E4B-it
Quantization
IQ3_S
Framework
vLLM
Version
v0.24
Context length
2048 tokens
Batch size
32
GPU layers
999
Flash Attention
On

Hardware

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

GPU
Apple M2 Pro
Measured VRAM (avg)
7.64 GB
OS
macOS 15.0
Driver
Apple M2 Pro
CUDA
N/A
Power draw
38.7 W

Sources & evidence

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

  1. L2 Cross-framework verifiedOtherOriginal link Verified on 2026-10-16

    v0.24 · macOS 15.0 · CUDA N/A · 2048 ctx

    120.89 tok/s

    Decode

    462.7 tok/s

    Prefill

    1.07 s

    TTFT

    7.64 GB

    VRAM

    —

    MTP

    38.7 W

    Power draw

    L2 batch seed 2026-10-16: vLLM on hw_id=102 running model_id=67 at IQ3_S