Question 1

Can I run Llama 3.1 70B on a Apple M1 Pro (10-core GPU)?

Accepted Answer

Yes — Apple M1 Pro (10-core GPU) runs Llama 3.1 70B fully on GPU at the Q2_K quantization. Full GPU inference — 32 GB VRAM meets the 32 GB recommendation.

Question 2

What quantization of Llama 3.1 70B should I use on a Apple M1 Pro (10-core GPU)?

Accepted Answer

For 32 GB VRAM on the Apple M1 Pro (10-core GPU), the Q2_K variant is the best fit. Estimated ~5 tokens/sec on the Q2_K quantization.

Question 3

How fast does Llama 3.1 70B run on Apple M1 Pro (10-core GPU)?

Accepted Answer

Roughly 5 tokens/sec for Q2_K. Real speed depends on context length, backend (Ollama, llama.cpp, LM Studio), and KV cache size.

Question 4

What if Apple M1 Pro (10-core GPU) 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_KBest fit	25 GB	27 GB	32 GB	8K / 128K	Full GPU	~5
Q3_K_M	33 GB	35 GB	40 GB	8K / 128K	Hybrid CPU+GPU	~2
Q4_K_M	40 GB	42 GB	48 GB	8K / 128K	Hybrid CPU+GPU	~2
Q5_K_M	48 GB	50 GB	56 GB	8K / 128K	Hybrid CPU+GPU	~1
Q8_0	74 GB	76 GB	80 GB	8K / 128K	Can't Run	—

Can I Run Llama 3.1 70B on Apple M1 Pro (10-core GPU)?

Share this matchup

Every Llama 3.1 70B quantization on Apple M1 Pro (10-core GPU)