How it works FLUX.1 Fill Dev?
FLUX.1 Fill Dev is an open-weights model by Black Forest Labs for editing existing images: it fills masked areas and extends the frame beyond original borders. This version is derived via guidance distillation from FLUX.1 Fill [pro], mirroring its filling approach. Edits are based on text prompts or references, leaving the rest of the frame untouched. Via BotHub, the model is accessible without VPN or foreign cards: pay with Russian cards in rubles, pay-as-you-go, and unused tokens do not expire. Access over 250 neural networks in one window, use a unified OpenAI-compatible API, enjoy AES-GCM data encryption, and benefit from contracts, invoices, EDI, and an admin panel with limits for teams. Useful for removing unwanted objects, replacing backgrounds or product details, extending vertical shots into horizontal banners, adapting layouts for multiple formats, or generating creative variations for testing.Frequently asked questions about FLUX.1 Fill Dev
You can use generated results for commercial purposes. You own all rights to the content you create. The only restriction: make sure your prompt does not include copyrighted third-party material. You are responsible for respecting the rights to any input data.
flux-fill-dev is a FLUX family model for inpainting and editing within an image. Upload a frame, mark an area, and describe what should appear there: remove an unwanted object, replace a background, extend a scene, or insert a detail. Suitable for retouching, product photos, and preparing creatives.
You get a raster image as output: the model fills the selected area and matches it to the original frame in terms of light, texture, and perspective. Specific resolution and format depend on request parameters and the source you uploaded; fixed values are not specified in our data.
No separate reasoning mode is noted in our data: it is a generative image model that immediately outputs results based on the description and mask. Therefore, think through the logic in your prompt — specify the object, material, lighting, and angle in detail. The request context is 4095 tokens.
Function calling and strict JSON output are not noted for this model in our data — its task is to return an image, not structured text. To embed it in your product, use the unified OpenAI-compatible BotHub API: one integration, and you change the model via a parameter in the request.
Images — yes, this is the main scenario: the model takes your frame as input and works in image-to-image mode, filling in the required area. Audio and video input are not noted in our data, so count on a combination of an image and a text description.
Nothing is recorded in our data regarding prompt language, so we cannot promise anything here — focus on a detailed scene description and an accurate mask. BotHub itself is fully in Russian: interface, support, payment with Russian cards in rubles, and access from the Russian Federation without VPN.