Question 1

Can I run Llama 3.2 1B on a Apple M3 Ultra?

Accepted Answer

Yes — Apple M3 Ultra runs Llama 3.2 1B fully on GPU at the FP16 quantization. Full GPU inference — 192 GB VRAM meets the 6 GB recommendation.

Question 2

What quantization of Llama 3.2 1B should I use on a Apple M3 Ultra?

Accepted Answer

For 192 GB VRAM on the Apple M3 Ultra, the FP16 variant is the best fit. Estimated ~320 tokens/sec on the FP16 quantization.

Question 3

How fast does Llama 3.2 1B run on Apple M3 Ultra?

Accepted Answer

Roughly 320 tokens/sec for FP16. Real speed depends on context length, backend (Ollama, llama.cpp, LM Studio), and KV cache size.

Question 4

What if Apple M3 Ultra is not enough for Llama 3.2 1B?

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
Q4_K_M	0.75 GB	1.5 GB	2 GB	8K / 128K	Full GPU	~853.3
Q8_0	1.3 GB	2 GB	4 GB	8K / 128K	Full GPU	~586.1
FP16Best fit	2.5 GB	3.5 GB	6 GB	8K / 128K	Full GPU	~320

Can I Run Llama 3.2 1B on Apple M3 Ultra?

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