Back to search results

Qwen3-8B · Q4_K_S

Start a discussion
Apple M2 Ultrallama.cpp v0.43L2 Cross-framework verified

This page aggregates 1 real-world runs of Qwen3-8B (Q4_K_S) on Apple M2 Ultra with llama.cpp, contributed by 1 independent source platforms; metrics are averages of published measurements.

108.67 tok/s

Decode

Decode speed

436.07 tok/s

Prefill

Prefill speed

2.13 s

TTFT

Time to first token

15.2 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 (current)Decode 108.67 · Prefill 436.07 ·
  2. llama.cpp · Q5_K_S Decode 87.67 · Prefill 476.02 ·
  3. Ollama · Q5_K_M Decode 79.98 · Prefill 403.29 ·
  4. Ollama · Q8_0 Decode 67.83 · Prefill 284.74 ·

Core figures

Decode (avg)
108.67 tok/s
Prefill (avg)
436.07 tok/s
TTFT (avg)
2.13 s
VRAM (avg)
15.2 GB
MTP acceptance rate
—
TTFB
0.87 GB
Power draw
47.1 W

Configuration

Member-level fields are taken from the most recent run

Model
Qwen3-8B
Quantization
Q4_K_S
Framework
llama.cpp
Version
v0.43
Context length
8192 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 M2 Ultra
Measured VRAM (avg)
15.2 GB
OS
macOS 15.0
Driver
Apple M2 Ultra
CUDA
N/A
Power draw
47.1 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

    v0.43 · macOS 15.0 · CUDA N/A · 8192 ctx

    108.67 tok/s

    Decode

    436.07 tok/s

    Prefill

    2.13 s

    TTFT

    15.2 GB

    VRAM

    —

    MTP

    47.1 W

    Power draw

    L2 batch seed 2026-10-16: llama.cpp on hw_id=103 running model_id=53 at Q4_K_S