This page answers Lmstudio Community Deepseek R1 0528 Qwen3 8B Mlx 4bit q6_k quantization queries with explicit calculations from our model requirement dataset and compatibility speed table.
Short answer: Lmstudio Community Deepseek R1 0528 Qwen3 8B Mlx 4bit typically needs around 7GB VRAM at Q6_K, and 9GB is safer for smoother usage.
Estimated between Q4 and Q8 using a weighted interpolation toward Q8 memory footprint.
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 |
Lmstudio Community Deepseek R1 0528 Qwen3 8B Mlx 4bit at Q6_K is estimated to require about 7GB VRAM minimum, with 9GB 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.
Q6_K is a balance point between memory usage and quality. If your GPU is below 7GB, consider lower-bit quantization; if you have extra VRAM, compare Q8/FP16 options for quality-sensitive workloads.