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Can the Apple M2 Ultra (192GB) run gpt-oss 120B?

Apple M2 Ultra (192GB) × gpt-oss 120B8K context
YesRuns fully on the GPU
Memory at Q8_0125.3 GB of 144 GB
Weights 124.1 GBKV cache 0.6 GBRuntime 0.6 GB
QuantQ8_0Near-lossless
Memory125.3 GBof 144 GB usable
Speed~89tokens 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

Yes. The Apple M2 Ultra (192GB) can run gpt-oss 120B fully in unified memory at Q8_0 (near-lossless), using about 125.3 GB of the 144 GB available, at roughly 89 tokens/second.

Try other context lengths

Run it with Ollama

With Ollama installed, one command downloads and starts gpt-oss 120B:

ollama run gpt-oss:120b

Ollama's default download is Q4_K_M (about 72 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 M2 Ultra (192GB)

Run it in the cloud

No Apple M2 Ultra (192GB)? Run gpt-oss 120B 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 144 GB the Apple M2 Ultra (192GB) can use. macOS lets the GPU use about 144 GB of the 192 GB unified memory by default.

QuantQualityMemoryFits?Speed
FP16Full quality234.8 GBToo big—
Q8_0Near-lossless125.3 GBFits~89 tok/s
Q6_KExcellent97 GBFits~115 tok/s
Q5_K_MVery good84.3 GBFits~132 tok/s
Q4_K_MGood, most popular72 GBFits~155 tok/s
Q3_K_MNoticeably degraded58.3 GBFits~193 tok/s
Q2_KHeavily degraded45 GBFits~251 tok/s

Measured speed from real Apple M2 Ultra (192GB) owners

Tokens per second that people measured on their own Apple M2 Ultra (192GB), next to our estimate.

No one has measured gpt-oss 120B on the Apple M2 Ultra (192GB) yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.

Have an Apple M2 Ultra (192GB)? Add your real speed

One command times gpt-oss 120B 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:120b

Windows (PowerShell)

$env:GPUFIT_MODEL="gpt-oss:120b"; irm https://gpufit.dev/bench.ps1 | iex

How the benchmark works

GPUs that run gpt-oss 120B comfortably

Models that run well on the Apple M2 Ultra (192GB)

Frequently asked questions

Can Apple M2 Ultra (192GB) run gpt-oss 120B?

Yes. The Apple M2 Ultra (192GB) can run gpt-oss 120B fully in unified memory at Q8_0 (near-lossless), using about 125.3 GB of the 144 GB available, at roughly 89 tokens/second.

How much VRAM does gpt-oss 120B need?

About 72 GB at Q4_K_M with 8,192 tokens of context, and about 234.8 GB at full FP16 precision.

How fast is gpt-oss 120B on the Apple M2 Ultra (192GB)?

Roughly 89 tokens per second at Q8_0, estimated from the Apple M2 Ultra (192GB)'s 800 GB/s memory bandwidth.