RTX 4090 meets the minimum VRAM requirement for Q4 inference of deepseek-ai/deepseek-coder-1.3b-instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 4090 can run deepseek-ai/deepseek-coder-1.3b-instruct with Q4 quantization. At approximately 226 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 22GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 2GB | 24GB | 226.49 tok/s | ✅ Fits comfortably |
| Q8 | 3GB | 24GB | 153.82 tok/s | ✅ Fits comfortably |
| FP16 | 6GB | 24GB | 79.10 tok/s | ✅ Fits comfortably |