Stable Diffusion vs Flux: Hardware Requirements Compared
Flux.1 from Black Forest Labs represents a generational leap in image quality over Stable Diffusion, but it comes with significantly higher hardware demands. Here's what you need to know.
VRAM Requirements at a Glance
| Model | Min VRAM | Recommended | Resolution |
|---|---|---|---|
| SD 1.5 | 4GB | 6GB | 512x512 |
| SDXL | 8GB | 12GB | 1024x1024 |
| SD 3.5 Large | 6GB (no T5) | 16GB (with T5) | 1024x1024 |
| Flux.1 Schnell (FP8) | 8GB | 12GB | 1024x1024 |
| Flux.1 Dev (FP16) | 16GB | 24GB | 1024x1024 |
The Quantization Factor
Flux.1 is a 12B parameter model — larger than most LLMs people run locally. In FP16, it requires 24GB VRAM. However, FP8 quantization cuts this in half to 12GB with minimal quality loss, and NF4 brings it down to 8GB.
Practical Recommendations
If you have 8GB VRAM (RTX 4060, RX 7600): Stick with SDXL or try Flux NF4 quantization. SD 1.5 runs comfortably with all extensions.
If you have 12-16GB VRAM (RTX 4070, RX 7800 XT): Flux.1 Schnell in FP8 is your sweet spot. 4-step generation means near-instant results.
If you have 24GB VRAM (RTX 4090): Full Flux.1 Dev in FP16 with no compromises. This is the optimal setup.
If your hardware falls short, cloud GPUs offer an alternative — services like RunPod and Vast.ai provide GPU access starting at $0.15/hour.
Explore compatible models for your hardware on our model browser.