The primary bottleneck in running the FLUX.1 Dev model (12B parameters) on an NVIDIA RTX 4080 SUPER is the VRAM limitation. FLUX.1 Dev, in FP16 precision, requires 24GB of VRAM. The RTX 4080 SUPER is equipped with 16GB of GDDR6X, leaving a deficit of 8GB. This means the model, in its native FP16 format, cannot be fully loaded onto the GPU, resulting in a 'FAIL' verdict. The memory bandwidth of 0.74 TB/s on the RTX 4080 SUPER is substantial, but it becomes irrelevant if the entire model cannot reside in VRAM. When the model exceeds VRAM capacity, the system resorts to swapping data between the GPU and system RAM, which drastically slows down performance due to the significantly lower bandwidth of system RAM compared to GDDR6X.
To run FLUX.1 Dev on the RTX 4080 SUPER, you'll need to employ quantization techniques to reduce the model's memory footprint. Consider using 8-bit or even 4-bit quantization. This will significantly reduce VRAM usage, potentially bringing it within the 16GB limit. However, be aware that quantization can lead to a slight reduction in model accuracy. Alternatively, explore using CPU offloading, but this will severely impact inference speed. If acceptable performance isn't achievable with these methods, consider using a GPU with more VRAM or exploring cloud-based GPU solutions.