Can the Apple M4 (16GB) run gpt-oss 20B?

Apple M4 (16GB) × gpt-oss 20B8K context
Yes, with heavy quantizationFits only at a low-quality quant
Memory at Q2_K8.8 GB of 10.7 GB
Weights 7.8 GBKV cache 0.4 GBRuntime 0.6 GB
QuantQ2_KHeavily degraded
Memory8.8 GBof 10.7 GB usable
Speed~53tokens per second
  1. FP16
  2. Q8_0
  3. Q6_K
  4. Q5_K_M
  5. Q4_K_M
  6. Q3_K_M
  7. Q2_K

Only just. gpt-oss 20B fits on the Apple M4 (16GB) at Q2_K, which costs noticeable quality. Expect about 53 tokens/second. A card with more memory is a better experience.

Run it with Ollama

Ollama's default gpt-oss:20b download is Q4_K_M, which needs about 13.7 GB, more than the 10.7 GB available. Download the Q2_K GGUF instead (LM Studio lists quants per model), or try a smaller context length.

New to this? Step-by-step setup for the Apple M4 (16GB)

Run it in the cloud

Want full quality? Run gpt-oss 20B on a bigger rented GPU.

Rent a cloud GPU by the hour. No upfront cost, stop any time. Not sure whether to rent or buy? Compare the cost.

Memory needed by quantization

At 8,192 tokens of context. The black line marks the 10.7 GB the Apple M4 (16GB) can use. macOS lets the GPU use about 10.7 GB of the 16 GB unified memory by default.

QuantQualityMemoryFits?Speed
FP16Full quality42.8 GBToo big—
Q8_0Near-lossless23.2 GBToo big—
Q6_KExcellent18.1 GBToo big—
Q5_K_MVery good15.9 GBToo big—
Q4_K_MGood, most popular13.7 GBToo big—
Q3_K_MNoticeably degraded11.2 GBToo big—
Q2_KHeavily degraded8.8 GBFits~53 tok/s

Frequently asked questions

Can Apple M4 (16GB) run gpt-oss 20B?

Only just. gpt-oss 20B fits on the Apple M4 (16GB) at Q2_K, which costs noticeable quality. Expect about 53 tokens/second. A card with more memory is a better experience.

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 M4 (16GB)?

Roughly 53 tokens per second at Q2_K, estimated from the Apple M4 (16GB)'s 120 GB/s memory bandwidth.