RTX 5090 meets the minimum VRAM requirement for Q4 inference of deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 5090 can run deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct with Q4 quantization. At approximately 294 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 28GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 4GB | 32GB | 294.12 tok/s | ✅ Fits comfortably |
| Q8 | 7GB | 32GB | 216.22 tok/s | ✅ Fits comfortably |
| FP16 | 15GB | 32GB | 109.12 tok/s | ✅ Fits comfortably |