Can I Run Llama 4 on Apple M2 Max?
Written by Jakub Rusinowski · Last updated September 29, 2026
Yes, but it's tight — Llama 4 Scout 17B at Q4_K_M needs 68.2 GB at 8K context (65.8 GB weights + 2.4 GB KV cache/overhead), leaving ~3.8 GB of the Apple M2 Max's 72 GB usable memory, at ~19 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 |
Llama 4 Scout 17B on the Apple M2 Max: VRAM by quantization
| Quant | VRAM needed | Fits 96 GB? | Max context | Whole PC |
|---|---|---|---|---|
| F16 | 220.4 GB | ✗ No | — | — |
| Q8_0 | 118.2 GB | ✗ No | — | — |
| Q6_K | 91.8 GB | ✗ No | — | — |
| Q5_K_M | 79.7 GB | ✗ No | — | — |
| Q4_K_M | 68.2 GB | ✓ Yes | 16K | — |
| Q3_K_M | 48.9 GB | ✓ Yes | 64K | — |
| Q2_K | 38.2 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 68.2 GB · 32K 73.1 GB ✗ · 128K 92.4 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? Llama 4 Scout 17B on 48 GB of system RAM, CPU only: runs, but it is tight.
Llama 4 Sizes That Fit the Apple M2 Max (at 8K context)
| Llama 4 Scout 17B | Q4_K_M · 68.2 GB at 8K context · ~19 tok/s (est.) |
Llama 4 needs ~68 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
Will Llama 4 run on the Apple M2 Max?
Yes, but it's tight — Llama 4 Scout 17B at Q4_K_M needs 68.2 GB at 8K context (65.8 GB weights + 2.4 GB KV cache/overhead), leaving ~3.8 GB of the Apple M2 Max's 72 GB usable memory, at ~19 tok/s (est.), with room for up to 16K context.
Which Llama 4 variant fits best on the Apple M2 Max?
Llama 4 Scout 17B at Q4_K_M quantization needs 68.2 GB at 8K context (65.8 GB weights + 2.4 GB KV cache/overhead), estimated ~19 tokens/sec, up to 16K context.
Every Llama 4 size on the Apple M2 Max
| Size | VRAM at 8K | Verdict | Speed |
|---|---|---|---|
| Llama 4 Maverick 17B | 243.9 GB | Does not fit | — |
| Llama 4 Scout 17B | 68.2 GB | Runs | ~19 tok/s |
Llama 4 on Other GPUs
- Llama 4 on NVIDIA RTX PRO 6000 Blackwell
- Llama 4 on NVIDIA A100 80GB (PCIe)
- Llama 4 on NVIDIA H100 80GB (PCIe)
- Llama 4 on Apple M4 Max
- Llama 4 on Apple M3 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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