Can the Apple M2 Pro (32GB) run gpt-oss 20B?
- FP16
- Q8_0
- Q6_K
- Q5_K_M
- Q4_K_M
- Q3_K_M
- Q2_K
Yes. The Apple M2 Pro (32GB) can run gpt-oss 20B fully in unified memory at Q6_K (excellent), using about 18.1 GB of the 21.4 GB available, at roughly 41 tokens/second.
Run it with Ollama
With Ollama installed, one command downloads and starts gpt-oss 20B:
ollama run gpt-oss:20bOllama's default download is Q4_K_M (about 13.7 GB here). You have room for Q6_K, which is excellent: pick that GGUF in LM Studio or from Hugging Face.
Run it in the cloud
No Apple M2 Pro (32GB)? Run gpt-oss 20B in the cloud.
Rent a cloud GPU by the hour. No upfront cost, stop any time.
Memory needed by quantization
At 8,192 tokens of context. The black line marks the 21.4 GB the Apple M2 Pro (32GB) can use. 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 | 42.8 GB | Too big | — | |
| Q8_0 | Near-lossless | 23.2 GB | Too big | — | |
| Q6_K | Excellent | 18.1 GB | Fits | ~41 tok/s | |
| Q5_K_M | Very good | 15.9 GB | Fits | ~47 tok/s | |
| Q4_K_M | Good, most popular | 13.7 GB | Fits | ~55 tok/s | |
| Q3_K_M | Noticeably degraded | 11.2 GB | Fits | ~68 tok/s | |
| Q2_K | Heavily degraded | 8.8 GB | Fits | ~89 tok/s |
GPUs that run gpt-oss 20B comfortably
Frequently asked questions
Can Apple M2 Pro (32GB) run gpt-oss 20B?
Yes. The Apple M2 Pro (32GB) can run gpt-oss 20B fully in unified memory at Q6_K (excellent), using about 18.1 GB of the 21.4 GB available, at roughly 41 tokens/second.
How much VRAM does gpt-oss 20B need?
About 13.7 GB at Q4_K_M with 8,192 tokens of context, and about 42.8 GB at full FP16 precision.
How fast is gpt-oss 20B on the Apple M2 Pro (32GB)?
Roughly 41 tokens per second at Q6_K, estimated from the Apple M2 Pro (32GB)'s 200 GB/s memory bandwidth.