This page answers Deepseek AI Deepseek R1 0528 q8 quantization queries with explicit calculations from our model requirement dataset and compatibility speed table.
Short answer: Deepseek AI Deepseek R1 0528 typically needs around 8GB VRAM at Q8, and 10GB is safer for smoother usage.
Exact Q8 requirement from model requirement data.
Throughput data below uses available compatibility measurements/estimates and is sorted by tokens per second for this model.
Need general guidance? Review full methodology.
| GPU | VRAM | Quantization | Speed | Compatibility | Buy |
|---|---|---|---|---|---|
| AMD Instinct MI300X | 192GB | Q8 | 668 tok/s | View full compatibility | Buy options |
| NVIDIA H200 SXM 141GB | 141GB | Q8 | 603 tok/s | View full compatibility | Buy options |
| NVIDIA H100 SXM5 80GB | 80GB | Q8 | 433 tok/s | View full compatibility | Buy options |
| AMD Instinct MI250X | 128GB | Q8 | 418 tok/s | View full compatibility | Buy options |
| NVIDIA H100 PCIe 80GB | 80GB | Q8 | 275 tok/s | View full compatibility | Buy options |
| RTX 5090 | 32GB | Q8 | 262 tok/s | View full compatibility | Buy options |
| NVIDIA A100 80GB SXM4 | 80GB | Q8 | 256 tok/s | View full compatibility | Buy options |
| AMD Instinct MI210 | 64GB | Q8 | 208 tok/s | View full compatibility | Buy options |
| NVIDIA A100 40GB PCIe | 40GB | Q8 | 199 tok/s | View full compatibility | Buy options |
| RTX 4090 | 24GB | Q8 | 158 tok/s | View full compatibility | Buy options |
| NVIDIA RTX 6000 Ada | 48GB | Q8 | 156 tok/s | View full compatibility | Buy options |
| NVIDIA L40 | 48GB | Q8 | 145 tok/s | View full compatibility | Buy options |
Deepseek AI Deepseek R1 0528 at Q8 is estimated to require about 8GB VRAM minimum, with 10GB recommended for smoother operation.
Start with AMD Instinct MI300X, NVIDIA H200 SXM 141GB, NVIDIA H100 SXM5 80GB and review each compatibility page for full speed and fit details.
Q8 is a balance point between memory usage and quality. If your GPU is below 8GB, consider lower-bit quantization; if you have extra VRAM, compare Q8/FP16 options for quality-sensitive workloads.