RTX 4090 meets the minimum VRAM requirement for Q4 inference of unsloth/Llama-3.2-3B-Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 4090 can run unsloth/Llama-3.2-3B-Instruct with Q4 quantization. At approximately 214 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 | 214.28 tok/s | ✅ Fits comfortably |
| Q8 | 3GB | 24GB | 157.17 tok/s | ✅ Fits comfortably |
| FP16 | 6GB | 24GB | 85.62 tok/s | ✅ Fits comfortably |