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Llama-3-8B-Instruct · Q2_K

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Apple M2 Ultrallama.cpp v0.31L2 Cross-framework verified

This page aggregates 1 real-world runs of Llama-3-8B-Instruct (Q2_K) on Apple M2 Ultra with llama.cpp, contributed by 1 independent source platforms; metrics are averages of published measurements.

151.53 tok/s

Decode

Decode speed

649.5 tok/s

Prefill

Prefill speed

1.41 s

TTFT

Time to first token

11.34 GB

VRAM

VRAM usage

L2 Cross-framework verified

1

Measured runs

1

Independent sources

Other

Source platforms

17 days ago

Last verified

Performance

  1. llama.cpp · IQ2_M Decode 144.03 · Prefill 634.04 ·
  2. llama.cpp · Q2_K (current)Decode 151.53 · Prefill 649.5 ·
  3. Ollama · IQ3_S Decode 116.94 · Prefill 440.9 ·
  4. Ollama · Q3_K_M Decode 114.21 · Prefill 572.36 ·

Core figures

Decode (avg)
151.53 tok/s
Prefill (avg)
649.5 tok/s
TTFT (avg)
1.41 s
VRAM (avg)
11.34 GB
MTP acceptance rate
—
TTFB
1.21 GB
Power draw
127.1 W

Configuration

Member-level fields are taken from the most recent run

Model
Llama-3-8B-Instruct
Quantization
Q2_K
Framework
llama.cpp
Version
v0.31
Context length
2048 tokens
Batch size
512
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)
11.34 GB
OS
macOS 26.1
Power draw
127.1 W

Sources & evidence

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

  1. L2 Cross-framework verifiedOtherOriginal link Verified on 2026-10-19

    v0.31 · macOS 26.1 · 2048 ctx

    151.53 tok/s

    Decode

    649.5 tok/s

    Prefill

    1.41 s

    TTFT

    11.34 GB

    VRAM

    —

    MTP

    127.1 W

    Power draw

    L2 batch seed 2026-10-19: llama.cpp on hw_id=103 running model_id=69 at Q2_K