This page answers Black Forest Labs Flux 1 Dev q6_k quantization queries with explicit calculations from our model requirement dataset and compatibility speed table.
Short answer: Black Forest Labs Flux 1 Dev 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 | 534 tok/s | View full compatibility | Buy options |
| NVIDIA H200 SXM 141GB | 141GB | Q8 | 482 tok/s | View full compatibility | Buy options |
| NVIDIA H100 SXM5 80GB | 80GB | Q8 | 347 tok/s | View full compatibility | Buy options |
| AMD Instinct MI250X | 128GB | Q8 | 334 tok/s | View full compatibility | Buy options |
| NVIDIA H100 PCIe 80GB | 80GB | Q8 | 220 tok/s | View full compatibility | Buy options |
| RTX 5090 | 32GB | Q8 | 210 tok/s | View full compatibility | Buy options |
| NVIDIA A100 80GB SXM4 | 80GB | Q8 | 204 tok/s | View full compatibility | Buy options |
| AMD Instinct MI210 | 64GB | Q8 | 166 tok/s | View full compatibility | Buy options |
| NVIDIA A100 40GB PCIe | 40GB | Q8 | 159 tok/s | View full compatibility | Buy options |
| RTX 4090 | 24GB | Q8 | 126 tok/s | View full compatibility | Buy options |
| NVIDIA RTX 6000 Ada | 48GB | Q8 | 125 tok/s | View full compatibility | Buy options |
| NVIDIA L40 | 48GB | Q8 | 116 tok/s | View full compatibility | Buy options |
Black Forest Labs Flux 1 Dev 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.