NVIDIA RTX 6000 Ada meets the minimum VRAM requirement for Q4 inference of RedHatAI/Meta-Llama-3.1-70B-Instruct-quantized.w4a16. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
NVIDIA RTX 6000 Ada can run RedHatAI/Meta-Llama-3.1-70B-Instruct-quantized.w4a16 with Q4 quantization. At approximately 62 tokens/second, you can expect Good speed - acceptable for interactive use.
You have 14GB headroom, which is sufficient for system overhead and smooth operation.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 34GB | 48GB | 62.31 tok/s | ✅ Fits comfortably |
| Q8 | 68GB | 48GB | 47.11 tok/s | ❌ Not recommended |
| FP16 | 137GB | 48GB | 24.74 tok/s | ❌ Not recommended |