Can the Apple M2 Pro (32GB) run Phi-3.5 Mini 3.8B?
Yes
QuantFP16Full quality
Memory11.5 GBof 21.4 GB
Speed~16tokens/s
Yes. The Apple M2 Pro (32GB) can run Phi-3.5 Mini 3.8B fully in unified memory at FP16 (full quality), using about 11.5 GB of the 21.4 GB available, at roughly 16 tokens/second.
Try other context lengths in the calculator →Memory needed by quantization
At 8,192 tokens of context. macOS lets the GPU use about 21.4 GB of the 32 GB unified memory by default.
| Quant | Quality | Memory | Fits? | Speed |
|---|---|---|---|---|
| FP16 | Full quality | 11.5 GB | Fits | ~16 tok/s |
| Q8_0 | Near-lossless | 7.9 GB | Fits | ~30 tok/s |
| Q6_K | Excellent | 7 GB | Fits | ~38 tok/s |
| Q5_K_M | Very good | 6.5 GB | Fits | ~44 tok/s |
| Q4_K_M | Good, most popular | 6.1 GB | Fits | ~52 tok/s |
| Q3_K_M | Noticeably degraded | 5.7 GB | Fits | ~64 tok/s |
| Q2_K | Heavily degraded | 5.3 GB | Fits | ~84 tok/s |
How to run Phi-3.5 Mini 3.8B on the Apple M2 Pro (32GB)
With Ollama installed, one command downloads and starts it:
ollama run phi3.5:3.8bOllama's default download is Q4_K_M (about 6.1 GB here). You have room for FP16, which is full quality: pick that GGUF in LM Studio or from Hugging Face.
GPUs that run Phi-3.5 Mini 3.8B comfortably
- NVIDIA RTX 4060 (8 GB)
- NVIDIA RTX 3070 (8 GB)
- NVIDIA RTX 3080 10GB
- NVIDIA RTX 3060 12GB
- NVIDIA RTX 4070 (12 GB)
Models that run well on the Apple M2 Pro (32GB)
Run it in the cloud
Don't want to buy hardware? Run Phi-3.5 Mini 3.8B on a rented GPU today.
Rent a cloud GPU by the hour. No upfront cost, cancel any time.