Question 1

Can I run Qwen3 0.6B on a Apple M2?

Accepted Answer

Yes — Apple M2 runs Qwen3 0.6B fully on GPU at the FP16 quantization. Full GPU inference — 24 GB VRAM meets the 1.6 GB recommendation.

Question 2

What quantization of Qwen3 0.6B should I use on a Apple M2?

Accepted Answer

For 24 GB VRAM on the Apple M2, the FP16 variant is the best fit. Estimated ~83.3 tokens/sec on the FP16 quantization.

Question 3

How fast does Qwen3 0.6B run on Apple M2?

Accepted Answer

Roughly 83.3 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 M2 is not enough for Qwen3 0.6B?

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	0.3 GB	0.3 GB	0.4 GB	8K / 8K	Full GPU	~266.7
Q5_K_M	0.4 GB	0.5 GB	0.5 GB	8K / 8K	Full GPU	~217.4
Q8_0	0.6 GB	0.7 GB	0.8 GB	8K / 8K	Full GPU	~158.7
FP16Best fit	1.2 GB	1.4 GB	1.6 GB	8K / 8K	Full GPU	~83.3

Can I Run Qwen3 0.6B on Apple M2?

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