Can I Run GPT-OSS on Apple M2 Max?
Written by Jakub Rusinowski · Last updated September 29, 2026
Yes, but it's tight — GPT-OSS 120B at Q4_K_M needs 71.6 GB at 8K context (70.5 GB weights + 1.1 GB KV cache/overhead), leaving ~0.4 GB of the Apple M2 Max's 72 GB usable memory, at ~56 tok/s (est.), with room for up to 16K context.
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Apple M2 Max Specs
| VRAM | 96 GB unified memory |
| Memory Bandwidth | 400 GB/s |
GPT-OSS 120B on the Apple M2 Max: VRAM by quantization
| Quant | VRAM needed | Fits 96 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 234.7 GB | ✗ No | — | — |
| Q8_0 | 125.2 GB | ✗ No | — | — |
| Q6_K | 96.9 GB | ✗ No | — | — |
| Q5_K_M | 83.9 GB | ✗ No | — | — |
| Q4_K_M | 71.6 GB | ✓ Yes | 16K | — |
| Q3_K_M | 50.9 GB | ✓ Yes | 128K | — |
| Q2_K | 39.5 GB | ✓ Yes | 128K | — |
Assumes an 8K-token context with an f16 KV cache. A longer window needs more; a quantized KV cache needs less. “Max context” is the largest window that still fits in 96 GB of unified memory. Figures are estimates from parameter count, quantization and memory bandwidth — the analyzer lets you tune KV-cache quant and context.
Context costs VRAM too. At Q4_K_M on the Apple M2 Max: 8K 71.6 GB · 32K 72.6 GB ✗ · 128K 76.2 GB ✗. Past 32K it no longer fits 96 GB — a q8_0 KV cache buys roughly half of that back, which the calculator will price for you.
No compatible GPU? GPT-OSS 120B on 96 GB of system RAM, CPU only: runs, but it is tight.
GPT-OSS Sizes That Fit the Apple M2 Max (at 8K context)
| GPT-OSS 120B | Q4_K_M · 71.6 GB at 8K context · ~56 tok/s (est.) |
| GPT-OSS 20B | MXFP4 · 12.1 GB at 8K context · ~82 tok/s (est.) |
GPT-OSS needs ~72 GB but this GPU has 96 GB. Rent a A100 (80 GB)-class GPU by the hour instead of buying one:
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Cloud rates verified 2026-07 — estimates, and marketplace prices vary. Buying price is GPU MSRP only, not a full PC.
FAQ
GPT-OSS on the Apple M2 Max — does it fit?
Yes, but it's tight — GPT-OSS 120B at Q4_K_M needs 71.6 GB at 8K context (70.5 GB weights + 1.1 GB KV cache/overhead), leaving ~0.4 GB of the Apple M2 Max's 72 GB usable memory, at ~56 tok/s (est.), with room for up to 16K context.
Which GPT-OSS variant fits best on the Apple M2 Max?
GPT-OSS 120B at Q4_K_M quantization needs 71.6 GB at 8K context (70.5 GB weights + 1.1 GB KV cache/overhead), estimated ~56 tokens/sec, up to 16K context.
Every GPT-OSS size on the Apple M2 Max
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| GPT-OSS 120B | 71.6 GB | Runs | ~56 tok/s |
| GPT-OSS 20B | 12.1 GB | Runs | ~82 tok/s |
GPT-OSS on Other GPUs
- GPT-OSS on NVIDIA RTX PRO 6000 Blackwell
- GPT-OSS on NVIDIA A100 80GB (PCIe)
- GPT-OSS on NVIDIA H100 80GB (PCIe)
- GPT-OSS on Apple M4 Max
Popular Models on the Apple M2 Max
VRAM Tier
Troubleshooting
- Ollama: "model requires more system memory than is available"
- Which GGUF quant should I download? (Q4 vs Q5 vs Q8)
Buying Guide
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