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Can the Apple M3 Pro (36GB) run gpt-oss 20B?

Apple M3 Pro (36GB) × gpt-oss 20B8K context
YesRuns fully on the GPU
Memory at Q8_023 GB of 24.1 GB
Weights 22.2 GBKV cache 0.2 GBRuntime 0.6 GB
QuantQ8_0Near-lossless
Speed~24tokens per second
Max context51Ktokens that fit at Q8_0
  1. FP16
  2. Q8_0
  3. Q6_K
  4. Q5_K_M
  5. Q4_K_M
  6. Q3_K_M
  7. Q2_K

Yes. The Apple M3 Pro (36GB) can run gpt-oss 20B fully in unified memory at Q8_0 (near-lossless), using about 23 GB of the 24.1 GB available, at roughly 24 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts gpt-oss 20B:

ollama run gpt-oss:20b

Ollama's default download is Q4_K_M (about 13.5 GB here). You have room for Q8_0, which is near-lossless: pick that GGUF in LM Studio or from Hugging Face.

New to this? Step-by-step setup for the Apple M3 Pro (36GB)

Run it in the cloud

No Apple M3 Pro (36GB)? Run gpt-oss 20B in the cloud.

Rent a cloud GPU by the hour. No upfront cost, stop any time.

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Memory needed by quantization

At 8,192 tokens of context. The black line marks the 24.1 GB the Apple M3 Pro (36GB) can use. macOS lets the GPU use about 24.1 GB of the 36 GB unified memory by default.

QuantQualityMemoryFits?Speed
FP16Full quality42.6 GBToo big—
Q8_0Near-lossless23 GBFits~24 tok/s
Q6_KExcellent17.9 GBFits~30 tok/s
Q5_K_MVery good15.7 GBFits~35 tok/s
Q4_K_MGood, most popular13.5 GBFits~41 tok/s
Q3_K_MNoticeably degraded11 GBFits~51 tok/s
Q2_KHeavily degraded8.6 GBFits~67 tok/s

Measured speed from real Apple M3 Pro (36GB) owners

Tokens per second that people measured on their own Apple M3 Pro (36GB), next to our estimate.

No one has measured gpt-oss 20B on the Apple M3 Pro (36GB) yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an Apple M3 Pro (36GB)? 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

Models that run well on the Apple M3 Pro (36GB)

Frequently asked questions

Can Apple M3 Pro (36GB) run gpt-oss 20B?

Yes. The Apple M3 Pro (36GB) can run gpt-oss 20B fully in unified memory at Q8_0 (near-lossless), using about 23 GB of the 24.1 GB available, at roughly 24 tokens/second.

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 M3 Pro (36GB)?

Roughly 24 tokens per second at Q8_0, estimated from the Apple M3 Pro (36GB)'s 150 GB/s memory bandwidth.