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Qwen3.5-4B · IQ2_M

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Apple M2 Prollama.cpp v0.42L2 Cross-framework verified

This page aggregates 1 real-world runs of Qwen3.5-4B (IQ2_M) on Apple M2 Pro with llama.cpp, contributed by 1 independent source platforms; metrics are averages of published measurements.

118.95 tok/s

Decode

Decode speed

519.35 tok/s

Prefill

Prefill speed

1.26 s

TTFT

Time to first token

6.47 GB

VRAM

VRAM usage

L2 Cross-framework verified

1

Measured runs

1

Independent sources

Other

Source platforms

2 days ago

Last verified

Performance

  1. llama.cpp · IQ2_M (current)Decode 118.95 · Prefill 519.35 ·
  2. llama.cpp · Q4_K_M Decode 94 · Prefill 499.11 ·
  3. Ollama · Q6_K Decode 70.16 · Prefill 240.68 ·

Core figures

Decode (avg)
118.95 tok/s
Prefill (avg)
519.35 tok/s
TTFT (avg)
1.26 s
VRAM (avg)
6.47 GB
MTP acceptance rate
—
TTFB
0.95 GB
Power draw
50.8 W

Configuration

Member-level fields are taken from the most recent run

Model
Qwen3.5-4B
Quantization
IQ2_M
Framework
llama.cpp
Version
v0.42
Context length
16384 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
Apple M2 Pro
Measured VRAM (avg)
6.47 GB
OS
macOS 15.0
Driver
Apple M2 Pro
CUDA
N/A
Power draw
50.8 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

    v0.42 · macOS 15.0 · CUDA N/A · 16384 ctx

    118.95 tok/s

    Decode

    519.35 tok/s

    Prefill

    1.26 s

    TTFT

    6.47 GB

    VRAM

    —

    MTP

    50.8 W

    Power draw

    L2 batch seed 2026-10-16: llama.cpp on hw_id=102 running model_id=48 at IQ2_M