Can I Run Llama 3.3 on MacBook Pro 16" (M4 Max, 48 GB)?
Superseded model. Llama 3.3 has been superseded by Llama 4. This page is kept for reference; the newer family is a better starting point.
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Written by Jakub Rusinowski · Last updated December 8, 2024
Yes, but it is tight
Yes, but it is tight — Llama 3.3 70B Instruct at Q3_K_M needs about 33.3 GB of the 36 GB usable on MacBook Pro 16" (M4 Max, 48 GB), leaving only ~2.7 GB before the runtime starts swapping. Expect ~9.3 tok/s (estimated), with room for about 8,192 tokens of context.
Confidence: medium · Recommended quantization: Q3_K_M · Estimated speed: ~9.3 tok/s
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) |
Llama 3.3 on MacBook Pro 16" (M4 Max, 48 GB): memory by quantization
| Quant | Memory needed | Fits 36 GB? | Max context | Est. speed | Download |
|---|
| F16 | 143.5 GB | ✗ No | — | — | 140 GB |
| Q8_0 | 77.9 GB | ✗ No | — | — | 74.4 GB |
| Q6_K | 60.9 GB | ✗ No | — | — | 57.4 GB |
| Q5_K_M | 53.1 GB | ✗ No | — | — | 49.6 GB |
| Q4_K_M | 45.7 GB | ✗ No | — | — | 42.3 GB |
| Q3_K_M | 33.3 GB | ✓ Yes | 8K | ~9.3 tok/s | 29.8 GB |
| Q2_K | 26.5 GB | ✓ Yes | 32K | ~11.9 tok/s | 23 GB |
What to watch out for
- Q3_K_M is the only quantization that fits, and it is a heavily degraded one — expect noticeably worse output than the same model at Q4_K_M. A smaller model at Q4 is usually the better trade.
- 1 larger variant of Llama 3.3 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 Llama 3.3 on MacBook Pro 16" (M4 Max, 48 GB)?
Yes, but it is tight — Llama 3.3 70B Instruct at Q3_K_M needs about 33.3 GB of the 36 GB usable on MacBook Pro 16" (M4 Max, 48 GB), leaving only ~2.7 GB before the runtime starts swapping. Expect ~9.3 tok/s (estimated), with room for about 8,192 tokens of context.
Which quantization of Llama 3.3 should I use on MacBook Pro 16" (M4 Max, 48 GB)?
Q3_K_M — it needs about 33.3 GB of the 36 GB available, downloads as roughly 29.8 GB, and runs at an estimated 9.3 tokens/sec with up to 8K of context.
What limits Llama 3.3 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
Other Models on MacBook Pro 16" (M4 Max, 48 GB)
Llama 3.3 on GPUs
What This Model Is Good At
Model & Tools
← Can I Run It? | Llama 3.3 model page | Check your hardware