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Qwen3-Coder-Next · Q5_K_S

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Apple M2 UltravLLM v0.33L2 Cross-framework verified

This page aggregates 1 real-world runs of Qwen3-Coder-Next (Q5_K_S) on Apple M2 Ultra with vLLM, contributed by 1 independent source platforms; metrics are averages of published measurements.

96.07 tok/s

Decode

Decode speed

412.07 tok/s

Prefill

Prefill speed

0.12 s

TTFT

Time to first token

1.05 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 · Q4_K_S Decode 104.58 · Prefill 471.99 ·
  2. vLLM · IQ1_S Decode 161.77 · Prefill 872.93 ·
  3. vLLM · Q5_K_S (current)Decode 96.07 · Prefill 412.07 ·

Core figures

Decode (avg)
96.07 tok/s
Prefill (avg)
412.07 tok/s
TTFT (avg)
0.12 s
VRAM (avg)
1.05 GB
MTP acceptance rate
—
TTFB
0.77 GB
Power draw
27.9 W

Configuration

Member-level fields are taken from the most recent run

Model
Qwen3-Coder-Next
Quantization
Q5_K_S
Framework
vLLM
Version
v0.33
Context length
4096 tokens
Batch size
16
GPU layers
999
Flash Attention
Off

Hardware

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

GPU
Apple M2 Ultra
Measured VRAM (avg)
1.05 GB
OS
macOS 15.0
Driver
Apple M2 Ultra
CUDA
N/A
Power draw
27.9 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

    v0.33 · macOS 15.0 · CUDA N/A · 4096 ctx

    96.07 tok/s

    Decode

    412.07 tok/s

    Prefill

    0.12 s

    TTFT

    1.05 GB

    VRAM

    —

    MTP

    27.9 W

    Power draw

    L2 batch seed 2026-10-16: vLLM on hw_id=103 running model_id=58 at Q5_K_S