Q: What quantization of Command R 35B should I use on a NVIDIA GeForce GTX 1650?

For 4 GB VRAM on the NVIDIA GeForce GTX 1650, the Q8_0 variant is the best fit. Estimated ~1 tokens/sec on the Q8_0 quantization.

Q: How fast does Command R 35B run on NVIDIA GeForce GTX 1650?

Roughly 1 tokens/sec for Q8_0. Real speed depends on context length, backend (Ollama, llama.cpp, LM Studio), and KV cache size.

Q: What if NVIDIA GeForce GTX 1650 is not enough for Command R 35B?

Consider upgrading to Apple M4 Pro (48 GB VRAM) which fits the recommended 44 GB target. Or pick a smaller quantization to stay on your current card.

Question 1

Can I run Command R 35B on a NVIDIA GeForce GTX 1650?

Accepted Answer

Sort of — NVIDIA GeForce GTX 1650 can run Command R 35B (Q8_0) only by spilling layers to RAM. Generation will be slow. CPU + GPU hybrid — not enough VRAM (4 GB < 39 GB min), but 64 GB RAM is sufficient. Expect significantly slower inference.

Question 2

What quantization of Command R 35B should I use on a NVIDIA GeForce GTX 1650?

Accepted Answer

For 4 GB VRAM on the NVIDIA GeForce GTX 1650, the Q8_0 variant is the best fit. Estimated ~1 tokens/sec on the Q8_0 quantization.

Question 3

How fast does Command R 35B run on NVIDIA GeForce GTX 1650?

Accepted Answer

Roughly 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 NVIDIA GeForce GTX 1650 is not enough for Command R 35B?

Accepted Answer

Consider upgrading to Apple M4 Pro (48 GB VRAM) which fits the recommended 44 GB target. Or pick a smaller quantization to stay on your current card.

Quantization	File Size	Min VRAM	Rec VRAM	Context	Verdict	Estimated tok/s
Q4_K_M	20 GB	22 GB	24 GB	4K / 128K	Hybrid CPU+GPU	~2
Q8_0Best fit	37 GB	39 GB	44 GB	4K / 128K	Hybrid CPU+GPU	~1

Can I Run Command R 35B on NVIDIA GeForce GTX 1650?

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Every Command R 35B quantization on NVIDIA GeForce GTX 1650

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