Question 1

Can I run Llama 3.1 70B on a Apple M2 Max?

Accepted Answer

Yes — Apple M2 Max runs Llama 3.1 70B fully on GPU at the Q8_0 quantization. Full GPU inference — 96 GB VRAM meets the 80 GB recommendation.

Question 2

What quantization of Llama 3.1 70B should I use on a Apple M2 Max?

Accepted Answer

For 96 GB VRAM on the Apple M2 Max, the Q8_0 variant is the best fit. Estimated ~5.1 tokens/sec on the Q8_0 quantization.

Question 3

How fast does Llama 3.1 70B run on Apple M2 Max?

Accepted Answer

Roughly 5.1 tokens/sec for Q8_0. Real speed depends on context length, backend (Ollama, llama.cpp, LM Studio), and KV cache size.

Question 4

What if Apple M2 Max is not enough for Llama 3.1 70B?

Accepted Answer

Try a smaller quantization variant or run on CPU + RAM with the trade-off of slower generation.

Quantization	File Size	Min VRAM	Rec VRAM	Context	Verdict	Estimated tok/s
Q2_K	25 GB	27 GB	32 GB	8K / 128K	Full GPU	~10
Q3_K_M	33 GB	35 GB	40 GB	8K / 128K	Full GPU	~8.4
Q4_K_M	40 GB	42 GB	48 GB	8K / 128K	Full GPU	~8
Q5_K_M	48 GB	50 GB	56 GB	8K / 128K	Full GPU	~7.2
Q8_0Best fit	74 GB	76 GB	80 GB	8K / 128K	Full GPU	~5.1

Can I Run Llama 3.1 70B on Apple M2 Max?

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