Can the MacBook Pro 16" M4 Max run gpt-oss-120b?
Not fully, but it's usable. gpt-oss-120b needs about 71.8 GB at Q4_K_M and the MacBook Pro 16" M4 Max has 48 GB - yet as a mixture-of-experts model it reads only ~5.1B parameters per token, so you can keep attention on the GPU and the experts in system RAM (llama.cpp --n-cpu-moe) and still get interactive speeds with 32 GB+ of RAM.
Every quantization
gpt-oss-120b (120.4B, 5.1B active) on 48 GB
| Quant | Weights | Needs | Fit | Est. speed |
|---|---|---|---|---|
| Q4_K_M | 70 GB | 71.8 GB | Too big | - |
| Q5_K_M | 85 GB | 86.8 GB | Too big | - |
| Q8_0 | 129 GB | 130.8 GB | Too big | - |
| FP16 | 241 GB | 242.8 GB | Too big | - |
Estimates. Needs = weights + 1.8 GB for KV cache and runtime at modest context. Speed is single-stream decode scaled from the MacBook Pro 16" M4 Max's 546 GB/s bandwidth (Estimated from memory bandwidth (llama.cpp decode)). Long contexts need more memory and run slower.
What to do instead
Two ways forward
Cheapest cards that run it
- Mac Studio M4 Ultra - 192 GB, ~$4,699
Models that fit the MacBook Pro 16" M4 Max
- Qwen3.6 35B A3B - 36B, 21 GB at Q4
- Qwen3.5 35B A3B - 36B, 21 GB at Q4
- dolphin-2.9.1-yi-1.5-34b - 34.4B, 20 GB at Q4
- Gemma 4 31B - 32.7B, 19 GB at Q4
Compare
Same model, other hardware - and other models on this card
gpt-oss-120b on other hardware
- RTX 6000D~202 tok/s
- DGX Spark (GB10)~35 tok/s
- RTX Spark N1X (128 GB)~35 tok/s
Also runs on the MacBook Pro 16" M4 Max
- Qwen3.6 35B A3B~119 tok/s
- Qwen3.5 35B A3B~119 tok/s
- dolphin-2.9.1-yi-1.5-34b~16 tok/s
- Gemma 4 31B~16 tok/s
- Qwen3 32B~16 tok/s
- GLM-4.7-Flash~121 tok/s
- Qwen3-30B-A3B-Instruct-2507~118 tok/s
- Qwen3.6 27B~20 tok/s
Frequently asked
Quick answers
Can the Apple MacBook Pro 16" M4 Max run gpt-oss-120b?
Not fully, but it's usable. gpt-oss-120b needs about 71.8 GB at Q4_K_M and the MacBook Pro 16" M4 Max has 48 GB - yet as a mixture-of-experts model it reads only ~5.1B parameters per token, so you can keep attention on the GPU and the experts in system RAM (llama.cpp --n-cpu-moe) and still get interactive speeds with 32 GB+ of RAM.
How much VRAM does gpt-oss-120b need?
About 70 GB of weights at Q4_K_M, 129 GB at Q8_0 and 241 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.
How fast is gpt-oss-120b on the MacBook Pro 16" M4 Max?
It doesn't fit in the MacBook Pro 16" M4 Max's memory, so speed depends on how many layers you offload to system RAM - typically single-digit tokens per second or lower.