Can the MacBook Pro 16" M4 Max run Llama 3.3 70B?

Just. Llama 3.3 70B at Q4_K_M needs about 41.8 GB of the MacBook Pro 16" M4 Max's 48 GB, running at an estimated 7.8 tok/s. Keep context short and close other GPU apps.

Memory
48 GB
Needs at Q4
41.8 GB
Headroom
6.2 GB
Speed (Q4_K_M)
~7.8 tok/s

Every quantization

Llama 3.3 70B (70B) on 48 GB

QuantWeightsNeedsFitEst. speed
Q4_K_M40 GB41.8 GBTight~7.8 tok/s
Q5_K_M48 GB49.8 GBToo big -
Q8_075 GB76.8 GBToo big -
FP16140 GB141.8 GBToo 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.

Run it

Copy, paste, go

ollama run llama3.3:70b
llama-server -hf bartowski/Llama-3.3-70B-Instruct-GGUF -ngl 99

Ollama pulls a Q4 build by default. Pick a larger quant only if the table above says it fits. Full Llama 3.3 70B details →

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Same model, other hardware - and other models on this card

Llama 3.3 70B on other hardware

Also runs on the MacBook Pro 16" M4 Max

Frequently asked

Quick answers

Can the Apple MacBook Pro 16" M4 Max run Llama 3.3 70B?

Just. Llama 3.3 70B at Q4_K_M needs about 41.8 GB of the MacBook Pro 16" M4 Max's 48 GB, running at an estimated 7.8 tok/s. Keep context short and close other GPU apps.

How much VRAM does Llama 3.3 70B need?

About 40 GB of weights at Q4_K_M, 75 GB at Q8_0 and 140 GB at FP16. Add roughly 1.8 GB for the KV cache and runtime at modest context lengths.

How fast is Llama 3.3 70B on the MacBook Pro 16" M4 Max?

Roughly 7.8 tokens per second at Q4_K_M (single user, llama.cpp-style decode). This is an estimate from the MacBook Pro 16" M4 Max's 546 GB/s memory bandwidth.