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Can the Apple M5 (16GB) run gpt-oss 20B?

Apple M5 (16GB) × gpt-oss 20B8K context
Yes, with heavy quantizationFits only at a low-quality quant
Memory at Q2_K8.6 GB of 10.7 GB
Weights 7.8 GBKV cache 0.2 GBRuntime 0.6 GB
QuantQ2_KHeavily degraded
Speed~68tokens per second
Max context90Ktokens that fit at Q2_K
  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 M5 (16GB) at Q2_K, which costs noticeable quality. Expect about 68 tokens/second. A card with more memory is a better experience.

Try other context lengths

Run it with Ollama

Ollama's default gpt-oss:20b download is Q4_K_M, which needs about 13.5 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 M5 (16GB)

Run it in the cloud

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

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Memory needed by quantization

At 8,192 tokens of context. The black line marks the 10.7 GB the Apple M5 (16GB) can use. macOS lets the GPU use about 10.7 GB of the 16 GB unified memory by default.

QuantQualityMemoryFits?Speed
FP16Full quality42.6 GBToo big—
Q8_0Near-lossless23 GBToo big—
Q6_KExcellent17.9 GBToo big—
Q5_K_MVery good15.7 GBToo big—
Q4_K_MGood, most popular13.5 GBToo big—
Q3_K_MNoticeably degraded11 GBToo big—
Q2_KHeavily degraded8.6 GBFits~68 tok/s

Measured speed from real Apple M5 (16GB) owners

Tokens per second that people measured on their own Apple M5 (16GB), next to our estimate.

No one has measured gpt-oss 20B on the Apple M5 (16GB) yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an Apple M5 (16GB)? Add your real speed

One command times gpt-oss 20B in your own Ollama, shows you exactly what it would send, and asks before sending anything. No sign-up, no personal data.

macOS and Linux

curl -fsSL https://gpufit.dev/bench.sh | sh -s -- gpt-oss:20b

Windows (PowerShell)

$env:GPUFIT_MODEL="gpt-oss:20b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run gpt-oss 20B comfortably

Check RTX 4060 Ti 16GB prices

Models that run well on the Apple M5 (16GB)

Frequently asked questions

Can Apple M5 (16GB) run gpt-oss 20B?

Only just. gpt-oss 20B fits on the Apple M5 (16GB) at Q2_K, which costs noticeable quality. Expect about 68 tokens/second. A card with more memory is a better experience.

How much VRAM does gpt-oss 20B need?

About 13.5 GB at Q4_K_M with 8,192 tokens of context, and about 42.6 GB at full FP16 precision.

How fast is gpt-oss 20B on the Apple M5 (16GB)?

Roughly 68 tokens per second at Q2_K, estimated from the Apple M5 (16GB)'s 153 GB/s memory bandwidth.