Question 1

Can I run DeepSeek Coder V2 Lite 16B on a Apple M2 Ultra?

Accepted Answer

Yes — Apple M2 Ultra runs DeepSeek Coder V2 Lite 16B fully on GPU at the Q4_K_M quantization. Full GPU inference — 192 GB VRAM meets the 16 GB recommendation.

Question 2

What quantization of DeepSeek Coder V2 Lite 16B should I use on a Apple M2 Ultra?

Accepted Answer

For 192 GB VRAM on the Apple M2 Ultra, the Q4_K_M variant is the best fit. Estimated ~67.4 tokens/sec on the Q4_K_M quantization.

Question 3

How fast does DeepSeek Coder V2 Lite 16B run on Apple M2 Ultra?

Accepted Answer

Roughly 67.4 tokens/sec for Q4_K_M. Real speed depends on context length, backend (Ollama, llama.cpp, LM Studio), and KV cache size.

Question 4

What if Apple M2 Ultra is not enough for DeepSeek Coder V2 Lite 16B?

Accepted Answer

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

Can I Run DeepSeek Coder V2 Lite 16B on Apple M2 Ultra?

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Every DeepSeek Coder V2 Lite 16B quantization on Apple M2 Ultra