Some Longcat-Image-Edit samples, is a limited, yet very useful model.
Modified model runs in 30 steps instead of 50, boosting speed for single-face edits.
A Reddit user shared a modified version of Longcat-Image-Edit, a model designed for face-aware image editing and inpainting. The reference faces are generated using Flux 1 Dev. The modified variant reduces steps from 50 to 30 and sets CFG scale to 1 (down from 2.5), trading some quality for speed. In testing, the model excels at single-face inpainting and reference + prompt tasks, producing results that the user describes as more natural than Ernie and aesthetically closer to ZIT than to Flux 2 Klein. However, it lacks the rich content library of Klein or ZIT, limiting its versatility.
Despite its strengths in single-face editing, the model fails with multiple reference faces, making its target audience very limited. The base version (unmodified) offers better quality but is too slow for iterative use, according to the user. This trade-off between speed and capability positions Longcat-Image-Edit as a niche tool for professionals who need fast, realistic, single-subject face edits without the overhead of larger models.
- Modified Longcat-Image-Edit runs 30 steps at CFG 1 instead of base 50 steps at CFG 2.5 for faster inference
- Handles single-face inpainting and reference+prompt well but fails with multiple faces
- Aesthetic rated as more natural than Ernie and closer to ZIT, but content library is sparse compared to Klein
Why It Matters
For single-subject face edits, this model offers a fast, natural alternative, but its limitations highlight the gap in multi-reference AI image editing.