Can I Run GPT-OSS on MacBook Pro 16" (M4 Max, 48 GB)?
Autor: Jakub Rusinowski · Ostatnia aktualizacja: 15 sierpnia 2026
Yes — comfortably
Yes, comfortably — GPT-OSS 20B at Q8_0 needs about 23.2 GB of the 36 GB usable on MacBook Pro 16" (M4 Max, 48 GB), leaving ~12.8 GB spare and running at ~61.8 tok/s (estimated), with room for about 131,072 tokens of context.
Confidence: high · Recommended quantization: Q8_0 · Estimated speed: ~61.8 tok/s
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MacBook Pro 16" (M4 Max, 48 GB) — what it gives a model
| Usable memory for models | 36 GB |
| Memory bandwidth | 546 GB/s |
| Form factor | Laptop |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
| Price | $3,999 (lib/data/laptops.ts (street price), checked 2026-07-06) |
GPT-OSS on MacBook Pro 16" (M4 Max, 48 GB): memory by quantization
| Quant | Memory needed | Fits 36 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 42.8 GB | ✗ No | — | — | 41.8 GB |
| Q8_0 | 23.2 GB | ✓ Yes | 128K | ~61.8 tok/s | 22.2 GB |
| Q6_K | 18.2 GB | ✓ Yes | 128K | ~75.4 tok/s | 17.1 GB |
| Q5_K_M | 15.8 GB | ✓ Yes | 128K | ~83.9 tok/s | 14.8 GB |
| Q4_K_M | 13.6 GB | ✓ Yes | 128K | ~93.8 tok/s | 12.6 GB |
| Q3_K_M | 9.9 GB | ✓ Yes | 128K | ~117.3 tok/s | 8.9 GB |
| Q2_K | 7.9 GB | ✓ Yes | 128K | ~136 tok/s | 6.9 GB |
Which GPT-OSS sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| GPT-OSS 120B | 71.6 GB | ✗ Too large | — |
| GPT-OSS 20B | 13.6 GB | ✓ Fits | ~93.8 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.
MacBook Pro M4 Max 48 GB limitations
- Unified memory is soldered and cannot be upgraded after purchase.
- macOS reserves a share of unified memory for the system, so not all 48 GB is available to a model.
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.
- 48 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 MacBook Pro 16" (M4 Max, 48 GB)?
Yes, comfortably — GPT-OSS 20B at Q8_0 needs about 23.2 GB of the 36 GB usable on MacBook Pro 16" (M4 Max, 48 GB), leaving ~12.8 GB spare and running at ~61.8 tok/s (estimated), with room for about 131,072 tokens of context.
Which quantization of GPT-OSS should I use on MacBook Pro 16" (M4 Max, 48 GB)?
Q8_0 — it needs about 23.2 GB of the 36 GB available, downloads as roughly 22.2 GB, and runs at an estimated 61.8 tokens/sec with up to 128K of context.
What limits GPT-OSS on MacBook Pro 16" (M4 Max, 48 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
- GPT-OSS on MacBook Pro M4 Max 128 GB
- GPT-OSS on MacBook Pro M4 Pro 24 GB
- GPT-OSS on MacBook Air M4 16 GB
Other Models on MacBook Pro 16" (M4 Max, 48 GB)
- Granite 3.0 on MacBook Pro 16" (M4 Max, 48 GB)
- IBM Granite 4.0 on MacBook Pro 16" (M4 Max, 48 GB)
- IBM Granite 4.1 on MacBook Pro 16" (M4 Max, 48 GB)
- IBM Granite 4.2 on MacBook Pro 16" (M4 Max, 48 GB)
- InternLM 3 on MacBook Pro 16" (M4 Max, 48 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