Claudiio Beck
Flux Kontext was only available as a paid service through several online APIs but on June 2025 the free version was released under the name of FLUX 1 Kontext Dev and can be run locally, aka, using Comfy UI or Diffusers.
What Kontext does is what most of us from the AI community were waiting for over the last years: generate changes to images while maintaining consistency. And that’s a game-changer in the history of generative AI.
See below some practical examples where I noted the Sampler technology used as well.
For a complete installation guide and basic workflows, refer to the official page here: https://docs.comfy.org/tutorials/flux/flux-1-kontext-dev
It is completely stunning how Kontext can handle the contextualization of its InPaint method and reading the whole image to a degree that can understand depth of field, noise, camera angle, character unique marks, posture, color grading and more.
Important to note that the engine Flux Kontext Dev provided by Black Forest Labs, the original author, does not allow NSFW, nudity, erotic or pornographic generations.
The downside is that Kontext not yet can easily change facial expressions. When trying expressions such as angry, surprised or sensual, it does not comply. Changing the Sampler might fix that. See example below.
While playing around and messing with prompting is fun and leads to visually stunning results, there must have a more serious and commercial application point of view, otherwise, the technology would render useless for businesses.
This is where the workflow of Kontext Dev lets us combine two images together and generates a single output with perfect matching colors and composition.
See the examples below.
Real photo of the product taken from Fashion Nova
Real photo of the product taken from Fashion Nova
Real photo of the product taken from Fashion Nova
The results are not yet optimal because the sandal is rendered twice with the same strap position, on the left and on the right feet. Plus, it still somehow has something way too artificial to be used commercially. Maybe with fine prompting or stacking some LORAs to the workflow could generate better results.
As take more time to study I will publish my findings on this website and LinkedIn.