Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic speed on NVIDIA L40 and quantization-level VRAM fit.
NVIDIA L40 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 L40 can run Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic with Q4 quantization. At approximately 33 tokens/second, you can expect Moderate speed - useful for batch processing.
VRAM usage will be very close to your GPU's limit. Consider closing other applications or using Q3 quantization for more margin.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 45GB | 48GB | 33.13 tok/s | ✅ Fits comfortably |
| Q8 | 90GB | 48GB | 23.19 tok/s | ❌ Not recommended |
| FP16 | 180GB | 48GB | 12.59 tok/s | ❌ Not recommended |
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NVIDIA L40 can run Redhatai Llama 3.2 90B Vision Instruct FP8 Dynamic at Q4 with an estimated 33 tok/s.
Q4 inference is estimated to need about 45GB 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.