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Qwen3-Embedding-0.6B · IQ2_M

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Apple M5 Pro64GBllama.cpp v0.31L2 Cross-framework verified

This page aggregates 1 real-world runs of Qwen3-Embedding-0.6B (IQ2_M) on Apple M5 Pro with llama.cpp, contributed by 1 independent source platforms; metrics are averages of published measurements.

301.75 tok/s

Decode

Decode speed

1,278.13 tok/s

Prefill

Prefill speed

0.83 s

TTFT

Time to first token

2.75 GB

VRAM

VRAM usage

L2 Cross-framework verified

1

Measured runs

1

Independent sources

Other

Source platforms

5 days ago

Last verified

Performance

  1. llama.cpp · IQ1_S Decode 286.68 · Prefill 1382.17 ·
  2. llama.cpp · IQ2_M (current)Decode 301.75 · Prefill 1278.13 ·
  3. Ollama · Q4_K_S Decode 342.8 · Prefill 1259.06 ·

Core figures

Decode (avg)
301.75 tok/s
Prefill (avg)
1,278.13 tok/s
TTFT (avg)
0.83 s
VRAM (avg)
2.75 GB
MTP acceptance rate
—
TTFB
2.41 GB
Power draw
68.4 W

Configuration

Member-level fields are taken from the most recent run

Model
Qwen3-Embedding-0.6B
Quantization
IQ2_M
Framework
llama.cpp
Version
v0.31
Context length
16384 tokens
Batch size
256
GPU layers
33
Flash Attention
On

Hardware

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

GPU
Apple M5 Pro
Nominal VRAM
64 GB
Measured VRAM (avg)
2.75 GB
OS
macOS 15.0
Driver
Apple M5 Pro
CUDA
N/A
Power draw
68.4 W

Sources & evidence

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

  1. L2 Cross-framework verifiedOtherOriginal link Verified on 2026-10-13

    v0.31 · macOS 15.0 · CUDA N/A · 16384 ctx

    301.75 tok/s

    Decode

    1,278.13 tok/s

    Prefill

    0.83 s

    TTFT

    2.75 GB

    VRAM

    —

    MTP

    68.4 W

    Power draw

    L2 batch seed 2026-10-13: llama.cpp on hw_id=27 running model_id=62 at IQ2_M