Can I Run GPT-OSS on Mac Studio (M4 Max, 64 GB)?
Written by Jakub Rusinowski · Last updated August 15, 2026
Yes — comfortably
Yes, comfortably — GPT-OSS 20B at Q8_0 needs about 23.4 GB of the 48 GB usable on Mac Studio (M4 Max, 64 GB), leaving ~24.6 GB spare and running at ~60.8 tok/s (estimated), with room for about 131,072 tokens of context.
Confidence: high · Recommended quantization: Q8_0 · Estimated speed: ~60.8 tok/s
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Mac Studio (M4 Max, 64 GB) — what it gives a model
| Usable memory for models | 48 GB |
| Memory bandwidth | 546 GB/s |
| Form factor | Desktop |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
GPT-OSS on Mac Studio (M4 Max, 64 GB): memory by quantization
| Quant | Memory needed | Fits 48 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 43 GB | ✓ Yes | 64K | ~36.1 tok/s | 41.8 GB |
| Q8_0 | 23.4 GB | ✓ Yes | 128K | ~60.8 tok/s | 22.2 GB |
| Q6_K | 18.3 GB | ✓ Yes | 128K | ~73.9 tok/s | 17.1 GB |
| Q5_K_M | 16 GB | ✓ Yes | 128K | ~82 tok/s | 14.8 GB |
| Q4_K_M | 13.8 GB | ✓ Yes | 128K | ~91.4 tok/s | 12.6 GB |
| Q3_K_M | 10.1 GB | ✓ Yes | 128K | ~113.6 tok/s | 8.9 GB |
| Q2_K | 8.1 GB | ✓ Yes | 128K | ~131.1 tok/s | 6.9 GB |
Which GPT-OSS sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| GPT-OSS 120B | 71.9 GB | ✗ Too large | — |
| GPT-OSS 20B | 13.8 GB | ✓ Fits | ~91.4 tok/s |
What to watch out for
- 1 larger variant of GPT-OSS does not fit and would need CPU offload or different hardware.
- Memory on this machine is not upgradeable, so the configuration you buy is the ceiling for every model you will ever run on it.
Mac Studio M4 Max 64 GB limitations
- Memory is soldered; the configuration chosen at purchase is permanent.
Recommended setup
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
How these numbers are calculated
- Memory need = quantized weights + KV cache at 8,192 tokens (f16) + 0.8 GB runtime overhead.
- 64 GB unified memory at 546 GB/s, shared between CPU and GPU.
- macOS reserves a share of unified memory for the system, so not all of it is available to a model.
- Throughput is a memory-bandwidth roofline estimate, not a measurement. It is labelled "estimated" everywhere it appears.
- KV cache is computed from this model's published attention configuration.
FAQ
Can I run GPT-OSS on Mac Studio (M4 Max, 64 GB)?
Yes, comfortably — GPT-OSS 20B at Q8_0 needs about 23.4 GB of the 48 GB usable on Mac Studio (M4 Max, 64 GB), leaving ~24.6 GB spare and running at ~60.8 tok/s (estimated), with room for about 131,072 tokens of context.
Which quantization of GPT-OSS should I use on Mac Studio (M4 Max, 64 GB)?
Q8_0 — it needs about 23.4 GB of the 48 GB available, downloads as roughly 22.2 GB, and runs at an estimated 60.8 tokens/sec with up to 128K of context.
What limits GPT-OSS on Mac Studio (M4 Max, 64 GB)?
Nothing binding — the model fits with headroom and generates at a usable speed on this hardware.
Which runtime should I use?
Ollama or LM Studio (Metal) — MLX for the fastest Apple-native throughput
Other Computers
Other Models on Mac Studio (M4 Max, 64 GB)
- Granite 3.0 on Mac Studio (M4 Max, 64 GB)
- IBM Granite 4.0 on Mac Studio (M4 Max, 64 GB)
- IBM Granite 4.1 on Mac Studio (M4 Max, 64 GB)
- IBM Granite 4.2 on Mac Studio (M4 Max, 64 GB)
- InternLM 3 on Mac Studio (M4 Max, 64 GB)
GPT-OSS on GPUs
- GPT-OSS on NVIDIA GeForce RTX 5080
- GPT-OSS on NVIDIA GeForce RTX 5070 Ti
- GPT-OSS on NVIDIA GeForce RTX 5070
- GPT-OSS on NVIDIA GeForce RTX 5060 Ti 16GB