Can I Run / GPT-OSS 20B / on Apple M5 Ultra (256GB)

Can I Run GPT-OSS 20B on a Apple M5 Ultra (256GB)?

Yes

Runs at full precision (fp16). Zero quality loss.

Model size
20.0B
GPU memory
256GB
Smallest quant
Q4_K_M
Best fit
fp16

5 quantizations fit your 256GB

QuantMin VRAMRecommendedFile sizeHeadroom
fp16BEST41.0 GB42.5 GB40.0 GB+215.0 GB
Q8_022.3 GB23.8 GB21.3 GB+233.8 GB
Q6_K17.5 GB19.0 GB16.5 GB+238.5 GB
Q5_K_M15.2 GB16.7 GB14.2 GB+240.8 GB
Q4_K_M13.1 GB14.6 GB12.1 GB+242.9 GB

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Full model details
GPT-OSS 20B

All quant variants, benchmark scores, and use-case tags.

Best models for this GPU
Apple M5 Ultra (256GB)

Top-ranked open-source models that fit in 256GB.

FAQ

Can the Apple M5 Ultra (256GB) run GPT-OSS 20B?

Yes. The Apple M5 Ultra (256GB)'s 256GB 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 256GB. 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.