MetaLlama 3.1 8B Instruct on Apple M2 Pro (16GB Unified)
M2 Pro (16GB Unified) runs Llama 3.1 8B Instruct at Q8_0 — 9 tok/s. Usable on 16 GB VRAM — see full quantization options below.
Model Size
8.03B
Device VRAM
16 GB
Bandwidth
200 GB/s
Quantization
Q8_0
Performance by Quantization
OwnRig currently has one published compatibility entry for Llama 3.1 8B Instruct on Apple M2 Pro (16GB Unified) at Q8_0. This is the best supported pairing we can stand behind today.
| Quantization | Speed | TTFT | Fits in VRAM | Rating | Confidence |
|---|---|---|---|---|---|
| Q8_0 | 9 tok/s | – | ✓ Yes | Acceptable | estimated |
Notes
Q8_0
Conservative estimate anchored to existing Apple Silicon results. Memory bandwidth and quantization size are the primary inference limiters.
About Llama 3.1 8B Instruct
Llama 3.1 8B Instruct (8.03B) is a chat, coding, ai coding, reasoning, multi-purpose model. Best-in-class 8B model. General capabilities with capable coding support. The go-to small model for local inference: fast, accurate, and well-supported across all inference engines.
View all Llama 3.1 8B Instruct hardware options →About Apple M2 Pro (16GB Unified)
Apple M2 Pro (16GB Unified) has 16 GB at 200 GB/s. Available in MacBook Pro 14" (2023), MacBook Pro 16" (2023).
See all models Apple M2 Pro (16GB Unified) can run →Estimate method: Conservative estimate anchored to m3-pro-18gb with bandwidth scaling, quantization-size adjustment, and generation damping. Reference hardware source: github.com (2026-04-18)
Performance varies by driver version, inference engine, quantization method, context length, and system configuration. Figures shown are estimates based on community benchmarks and may not reflect your exact setup. Product names are trademarks of their respective owners. OwnRig is independent and not affiliated with any hardware or AI model provider.