Can I Run GPT-OSS 20B on a Apple M4 Max (64GB)?
Runs at full precision (fp16). Zero quality loss.
5 quantizations fit your 64.0GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| fp16BEST | 41.0 GB | 42.5 GB | 40.0 GB | +23.0 GB |
| Q8_0 | 22.3 GB | 23.8 GB | 21.3 GB | +41.8 GB |
| Q6_K | 17.5 GB | 19.0 GB | 16.5 GB | +46.5 GB |
| Q5_K_M | 15.2 GB | 16.7 GB | 14.2 GB | +48.8 GB |
| Q4_K_M | 13.1 GB | 14.6 GB | 12.1 GB | +50.9 GB |
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Top-ranked open-source models that fit in 64.0GB.
FAQ
Can the Apple M4 Max (64GB) run GPT-OSS 20B?
Yes. The Apple M4 Max (64GB)'s 64.0GB of unified memory is enough to run GPT-OSS 20B at fp16 quantization (41.0GB required).
What's the best quantization to use?
fp16 is the highest-precision quantization that fits in your 64.0GB. It uses about 41.0GB of memory and 42.5GB recommended for comfortable inference.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.