Can I Run Llama 4 on MacBook Pro 16" (M4 Max, 128 GB)?
作者： Jakub Rusinowski · 最后更新： 2025年4月5日
Yes, but it is tight
Yes, but it is tight — Llama 4 Scout 17B at Q6_K needs about 91.8 GB of the 96 GB usable on MacBook Pro 16" (M4 Max, 128 GB), leaving only ~4.2 GB before the runtime starts swapping. Expect ~19.1 tok/s (estimated), with room for about 16,384 tokens of context.
Confidence: medium · Recommended quantization: Q6_K · Estimated speed: ~19.1 tok/s
Get a personalized upgrade path →
作为亚马逊联盟成员，我们从符合条件的购买中获得收入。云 GPU 链接为推荐链接——我们可能获得佣金，您无需额外付费。
MacBook Pro 16" (M4 Max, 128 GB) — what it gives a model
| Usable memory for models | 96 GB |
| Memory bandwidth | 546 GB/s |
| Form factor | Laptop |
| Operating system | macOS |
| Memory upgradeable | No — soldered |
Llama 4 on MacBook Pro 16" (M4 Max, 128 GB): memory by quantization
| Quant | Memory needed | Fits 96 GB? | Max context | Est. speed | Download |
|---|---|---|---|---|---|
| F16 | 220.4 GB | ✗ No | — | — | 218 GB |
| Q8_0 | 118.2 GB | ✗ No | — | — | 115.8 GB |
| Q6_K | 91.8 GB | ✓ Yes | 16K | ~19.1 tok/s | 89.4 GB |
| Q5_K_M | 79.7 GB | ✓ Yes | 64K | ~21.8 tok/s | 77.3 GB |
| Q4_K_M | 68.2 GB | ✓ Yes | 128K | ~25 tok/s | 65.8 GB |
| Q3_K_M | 48.9 GB | ✓ Yes | 128K | ~33.4 tok/s | 46.5 GB |
| Q2_K | 38.2 GB | ✓ Yes | 256K | ~41 tok/s | 35.8 GB |
Which Llama 4 sizes fit
| Variant | Needs at Q4_K_M | Fits? | Est. speed |
|---|---|---|---|
| Llama 4 Maverick 17B | 243.9 GB | ✗ Too large | — |
| Llama 4 Scout 17B | 68.2 GB | ✓ Fits | ~25 tok/s |
What to watch out for
- 1 larger variant of Llama 4 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 128 GB limitations
- Unified memory is soldered — the 128 GB decision is permanent and cannot be upgraded later.
- Sustained decode speed on battery is materially below the plugged-in figures quoted here.
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.
- 128 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 Llama 4 on MacBook Pro 16" (M4 Max, 128 GB)?
Yes, but it is tight — Llama 4 Scout 17B at Q6_K needs about 91.8 GB of the 96 GB usable on MacBook Pro 16" (M4 Max, 128 GB), leaving only ~4.2 GB before the runtime starts swapping. Expect ~19.1 tok/s (estimated), with room for about 16,384 tokens of context.
Which quantization of Llama 4 should I use on MacBook Pro 16" (M4 Max, 128 GB)?
Q6_K — it needs about 91.8 GB of the 96 GB available, downloads as roughly 89.4 GB, and runs at an estimated 19.1 tokens/sec with up to 16K of context.
What limits Llama 4 on MacBook Pro 16" (M4 Max, 128 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 Models on MacBook Pro 16" (M4 Max, 128 GB)
- Llama 4.5 on MacBook Pro 16" (M4 Max, 128 GB)
- Magistral Small on MacBook Pro 16" (M4 Max, 128 GB)
- MiniCPM-V on MacBook Pro 16" (M4 Max, 128 GB)
- MiniMax M2.5 on MacBook Pro 16" (M4 Max, 128 GB)
- MiniMax M2.7 on MacBook Pro 16" (M4 Max, 128 GB)
Llama 4 on GPUs
- Llama 4 on NVIDIA GeForce RTX 5090
- Llama 4 on NVIDIA GeForce RTX 4090
- Llama 4 on Apple M4 Max
- Llama 4 on Apple M4