Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic speed on NVIDIA H100 PCIe 80GB and quantization-level VRAM fit.
NVIDIA H100 PCIe 80GB meets the minimum VRAM requirement for Q4 inference of Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA H100 PCIe 80GB can run Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic with Q4 quantization. At approximately 63 tokens/second, you can expect Good speed - acceptable for interactive use.
You have 35GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 45GB | 80GB | 62.85 tok/s | ✅ Fits comfortably |
| Q8 | 90GB | 80GB | 44.00 tok/s | ❌ Not recommended |
| FP16 | 180GB | 80GB | 23.88 tok/s | ❌ Not recommended |
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NVIDIA H100 PCIe 80GB can run Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic at Q4 with an estimated 63 tok/s.
Q4 inference is estimated to need about 45GB VRAM on this page, while NVIDIA H100 PCIe 80GB has 80GB available.
If you need more speed or context headroom, compare alternative GPUs below and check higher-tier VRAM options.