Which AI models can the Apple M3 Max (64GB) run?
- 64 GB unified memory
- 400 GB/s bandwidth
- Apple
Every model we track, checked against the Apple M3 Max (64GB) at 8K context.
| Model | Runs? | Best fit |
|---|---|---|
| Llama 3.2 1B | Yes | FP16 · ~3.3 GB · ~97 tok/s |
| Llama 3.2 3B | Yes | FP16 · ~8 GB · ~37 tok/s |
| Llama 3.1 8B | Yes | FP16 · ~17.7 GB · ~15 tok/s |
| Llama 3.1 70B | Yes | Q4_K_M · ~46.1 GB · ~6 tok/s |
| Qwen2.5 7B | Yes | FP16 · ~16.3 GB · ~16 tok/s |
| Qwen2.5 14B | Yes | FP16 · ~31.6 GB · ~8 tok/s |
| Qwen2.5 32B | Yes | Q8_0 · ~37.6 GB · ~7 tok/s |
| Qwen2.5 72B | Yes | Q4_K_M · ~47.4 GB · ~5 tok/s |
| Qwen3 8B | Yes | FP16 · ~18.2 GB · ~15 tok/s |
| Qwen3 30B-A3B | Yes | Q8_0 · ~33.8 GB · ~68 tok/s |
| DeepSeek R1 Distill Qwen 32B | Yes | Q8_0 · ~37.6 GB · ~7 tok/s |
| Mistral 7B v0.3 | Yes | FP16 · ~16.2 GB · ~17 tok/s |
| Mistral Nemo 12B | Yes | FP16 · ~26.3 GB · ~10 tok/s |
| Mistral Small 24B | Yes | Q8_0 · ~27 GB · ~10 tok/s |
| Mixtral 8x7B | Yes | Q6_K · ~40 GB · ~23 tok/s |
| Gemma 2 9B | Yes | FP16 · ~21.9 GB · ~13 tok/s |
| Gemma 2 27B | Yes | Q8_0 · ~32.6 GB · ~8 tok/s |
| Gemma 3 4B | Yes | FP16 · ~10.3 GB · ~28 tok/s |
| Gemma 3 12B | Yes | FP16 · ~28.2 GB · ~10 tok/s |
| Gemma 3 27B | Yes | Q8_0 · ~33.9 GB · ~8 tok/s |
| Phi-3.5 Mini 3.8B | Yes | FP16 · ~11.5 GB · ~31 tok/s |
| Phi-4 14B | Yes | FP16 · ~31.7 GB · ~8 tok/s |
| Qwen3 4B | Yes | FP16 · ~9.8 GB · ~30 tok/s |
| Qwen3 14B | Yes | FP16 · ~31.5 GB · ~8 tok/s |
| Qwen3 32B | Yes | Q8_0 · ~37.6 GB · ~7 tok/s |
| Qwen3 Coder 30B-A3B | Yes | Q8_0 · ~33.8 GB · ~68 tok/s |
| gpt-oss 20B | Yes | FP16 · ~42.8 GB · ~33 tok/s |
| gpt-oss 120B | Yes, with heavy quantization | Q2_K · ~45 GB · ~125 tok/s |
| Llama 4 Scout 17B-16E | Yes, with heavy quantization | Q2_K · ~43.1 GB · ~38 tok/s |
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