Q: What quantization of StarCoder2 7B should I use on a NVIDIA GeForce GTX 1650?

For 4 GB VRAM on the NVIDIA GeForce GTX 1650, the Q4_K_M variant is the best fit. Estimated ~10 tokens/sec on the Q4_K_M quantization.

Q: How fast does StarCoder2 7B run on NVIDIA GeForce GTX 1650?

Roughly 10 tokens/sec for Q4_K_M. 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 StarCoder2 7B?

Consider upgrading to NVIDIA GeForce RTX 4060 Ti 8GB (8 GB VRAM) which fits the recommended 8 GB target. Or pick a smaller quantization to stay on your current card.

Question 1

Can I run StarCoder2 7B on a NVIDIA GeForce GTX 1650?

Accepted Answer

Sort of — NVIDIA GeForce GTX 1650 can run StarCoder2 7B (Q4_K_M) only by spilling layers to RAM. Generation will be slow. CPU + GPU hybrid — not enough VRAM (4 GB < 5 GB min), but 64 GB RAM is sufficient. Expect significantly slower inference.

Question 2

What quantization of StarCoder2 7B should I use on a NVIDIA GeForce GTX 1650?

Accepted Answer

For 4 GB VRAM on the NVIDIA GeForce GTX 1650, the Q4_K_M variant is the best fit. Estimated ~10 tokens/sec on the Q4_K_M quantization.

Question 3

How fast does StarCoder2 7B run on NVIDIA GeForce GTX 1650?

Accepted Answer

Roughly 10 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 NVIDIA GeForce GTX 1650 is not enough for StarCoder2 7B?

Accepted Answer

Consider upgrading to NVIDIA GeForce RTX 4060 Ti 8GB (8 GB VRAM) which fits the recommended 8 GB target. Or pick a smaller quantization to stay on your current card.

Can I Run StarCoder2 7B on NVIDIA GeForce GTX 1650?

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Every StarCoder2 7B quantization on NVIDIA GeForce GTX 1650

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