MetaLlama 3.2 1B Instruct on Apple M4 (16GB Unified)
Yes — M4 (16GB Unified) runs Llama 3.2 1B Instruct excellently at Q8_0 — 45 tok/s. 16 GB VRAM with plenty of headroom.
Model Size
1.24B
Device VRAM
16 GB
Bandwidth
120 GB/s
Quantization
Q8_0
Performance by Quantization
OwnRig currently has one published compatibility entry for Llama 3.2 1B Instruct on Apple M4 (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 | 45 tok/s | 100ms | ✓ Yes | Excellent | estimated |
Notes
Q8_0
M4 base chip: ~0.5x M4 Pro performance due to lower memory bandwidth.
About Llama 3.2 1B Instruct
Llama 3.2 1B Instruct (1.24B) is a chat, coding model. The smallest Llama model. Runs on integrated GPUs and even CPUs. Useful for basic classification, simple Q&A, and as a draft model for speculative decoding. Limited reasoning capability.
View all Llama 3.2 1B Instruct hardware options →About Apple M4 (16GB Unified)
Apple M4 (16GB Unified) has 16 GB at 120 GB/s. Available in Mac Mini, MacBook Pro 14", MacBook Air 13", MacBook Air 15", iPad Pro.
See all models Apple M4 (16GB Unified) can run →Estimate method: Estimated from M4 Pro benchmarks scaled by memory bandwidth ratio (120/273 GB/s). Reference hardware source: github.com (2026-03-14)
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.