Google Gemma 2 2B It speed on NVIDIA A100 80GB SXM4 and quantization-level VRAM fit.
NVIDIA A100 80GB SXM4 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 A100 80GB SXM4 can run Google Gemma 2 2B It with Q4 quantization. At approximately 350 tokens/second, you can expect Excellent speed - conversational response times under 1 second.
You have 79GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 1GB | 80GB | 350.48 tok/s | ✅ Fits comfortably |
| Q8 | 2GB | 80GB | 245.33 tok/s | ✅ Fits comfortably |
| FP16 | 4GB | 80GB | 133.18 tok/s | ✅ Fits comfortably |
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NVIDIA A100 80GB SXM4 can run Google Gemma 2 2B It at Q4 with an estimated 350 tok/s.
Q4 inference is estimated to need about 1GB VRAM on this page, while NVIDIA A100 80GB SXM4 has 80GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.