RTX 4090 meets the minimum VRAM requirement for Q4 inference of unsloth/Llama-3.2-1B-Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 4090 can run unsloth/Llama-3.2-1B-Instruct with Q4 quantization. At approximately 218 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 23GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 1GB | 24GB | 217.52 tok/s | ✅ Fits comfortably |
| Q8 | 1GB | 24GB | 158.64 tok/s | ✅ Fits comfortably |
| FP16 | 2GB | 24GB | 77.50 tok/s | ✅ Fits comfortably |