MetaLlama 3.2 1B Instruct on Apple M2 (8GB Unified)
Yes — M2 (8GB Unified) handles Llama 3.2 1B Instruct well at Q8_0 — 22 tok/s. Solid daily-driver performance on 8 GB VRAM.
Model Size
1.24B
Device VRAM
8 GB
Bandwidth
100 GB/s
Quantization
Q8_0
Performance by Quantization
OwnRig currently has one published compatibility entry for Llama 3.2 1B Instruct on Apple M2 (8GB 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 | 22 tok/s | – | ✓ Yes | Good | estimated |
Notes
Q8_0
Conservative estimate. Uses Q8_0 (1.5GB), the highest-quality format that fits within ~5.5GB usable memory.
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 M2 (8GB Unified)
Apple M2 (8GB Unified) has 8 GB at 100 GB/s. Available in MacBook Air 13" (2022), MacBook Air 15" (2023), MacBook Pro 13" (2022).
See all models Apple M2 (8GB Unified) can run →Estimate method: Conservative estimate anchored to m4-16gb 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.