RTX 4090 meets the minimum VRAM requirement for Q4 inference of LiquidAI/LFM2-1.2B. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 4090 can run LiquidAI/LFM2-1.2B with Q4 quantization. At approximately 220 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 | 220.33 tok/s | ✅ Fits comfortably |
| Q8 | 2GB | 24GB | 161.60 tok/s | ✅ Fits comfortably |
| FP16 | 4GB | 24GB | 79.75 tok/s | ✅ Fits comfortably |