Google Gemma 2 2B It speed on NVIDIA L40 and quantization-level VRAM fit.
NVIDIA L40 meets the minimum VRAM requirement for Q4 inference of Google Gemma 2 2B It. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA L40 can run Google Gemma 2 2B It with Q4 quantization. At approximately 199 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 47GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 1GB | 48GB | 198.76 tok/s | ✅ Fits comfortably |
| Q8 | 2GB | 48GB | 139.13 tok/s | ✅ Fits comfortably |
| FP16 | 4GB | 48GB | 75.53 tok/s | ✅ Fits comfortably |
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NVIDIA L40 can run Google Gemma 2 2B It at Q4 with an estimated 199 tok/s.
Q4 inference is estimated to need about 1GB VRAM on this page, while NVIDIA L40 has 48GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.