作者： Jakub Rusinowski · 最后更新： 2026年7月12日
Up to 32 GB unified memory. 52 t/s on 8B models. Handles 14B models at Q4 comfortably. Excellent battery life — runs AI tasks at under 30W total system power.
| VRAM | 32 GB unified memory |
| Memory Bandwidth | 200 GB/s |
| TDP | 30 W |
| Architecture | ARM, 5nm TSMC |
| Release Year | 2023 |
| MSRP at Launch | $1,999 |
| Inference Speed (Llama 3.1 8B Q4_K_M) | 13–26 tok/s (estimated) |
| Inference Speed (Llama 3.3 70B Q4_K_M) | Does not fit — needs ~44 GB of 24 GB usable |
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All models below run comfortably in 32 GB unified memory with Q4_K_M quantization.
| Llama 3.1 Family | Llama 3.1 8B Instruct · 6 GB VRAM · Q4_K_M · ollama run llama3.1 |
| Llama 3.2 Family | Llama 3.2 11B Vision Instruct · 7 GB VRAM · Q4_K_M · llama-3-2 |
| Qwen 3 | Qwen 3 32B · 21 GB VRAM · Q4_K_M · ollama run qwen3:32b |
| Gemma 3 | Gemma 3 27B Instruct · 17 GB VRAM · Q4_K_M · ollama run gemma3:27b |
| Phi-4 Mini | Phi-4 Mini (3.8B) · 3 GB VRAM · Q4_K_M · ollama run phi4-mini |
| Mistral Family | Mistral Small 3 (24B) · 15 GB VRAM · Q4_K_M · ollama run mistral-small |
| DeepSeek R1 | DeepSeek R1 Distill Qwen 32B · 20 GB VRAM · Q4_K_M · ollama run deepseek-r1:32b |
Install Ollama then run the recommended model for this GPU:
ollama run qwen3:14b
Yes — the Apple M2 Pro has 32 GB unified memory and runs Up to 32 GB unified memory. 52 t/s on 8B models. Handles 14B models at Q4 comfortably. Excellent battery life — runs AI
The Apple M2 Pro is estimated to run Llama 3.1 8B at 13–26 tok/s with Q4_K_M quantization. Llama 3.3 70B does not fit: it needs about 44 GB against 24 GB usable. These are modelled estimates, not measurements — see /en/methodology.
With 32 GB you can run: Llama 3.1 Family, Llama 3.2 Family, Qwen 3, Gemma 3, Phi-4 Mini. Use Ollama for the easiest setup: ollama run qwen3:14b.
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