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Llama-3-8B-Instruct · Q4_K_S
Apple M5 Ultra512GBllama.cpp v0.36L2 Cross-framework verified
This page aggregates 1 real-world runs of Llama-3-8B-Instruct (Q4_K_S) on Apple M5 Ultra with llama.cpp, contributed by 1 independent source platforms; metrics are averages of published measurements.
115.5 tok/s
Decode
Decode speed
509.11 tok/s
Prefill
Prefill speed
2.4 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
17 days ago
Last verified
Performance
- llama.cpp · IQ2_M Decode 145.48 · Prefill 672.26 ·
- llama.cpp · Q4_K_S (current)Decode 115.5 · Prefill 509.11 ·
- Ollama · IQ3_XS Decode 140.68 · Prefill 755.32 ·
Core figures
- Decode (avg)
- 115.5 tok/s
- Prefill (avg)
- 509.11 tok/s
- TTFT (avg)
- 2.4 s
- VRAM (avg)
- 15.2 GB
- MTP acceptance rate
- —
- TTFB
- 0.92 GB
- Power draw
- 114.2 W
Configuration
Member-level fields are taken from the most recent run
- Model
- Llama-3-8B-Instruct
- Quantization
- Q4_K_S
- Framework
- llama.cpp
- Version
- v0.36
- Context length
- 2048 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 M5 Ultra
- Nominal VRAM
- 512 GB
- Measured VRAM (avg)
- 15.2 GB
- OS
- macOS 26.1
- Power draw
- 114.2 W
Sources & evidence
1 measured records in total, each traceable to its original source
v0.36 · macOS 26.1 · 2048 ctx
115.5 tok/s
Decode
509.11 tok/s
Prefill
2.4 s
TTFT
15.2 GB
VRAM
—
MTP
114.2 W
Power draw
L2 batch seed 2026-10-19: llama.cpp on hw_id=29 running model_id=69 at Q4_K_S