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FIBO-Edit on Replicate changes an existing image from a text instruction, with an optional mask for edits limited to a selected area. To try it, provide an image, describe the change, review the generated result, and refine the instruction or inputs as needed. Replicate lists the hosted model at $0.04 per output image as of October 7, 2026; access to that endpoint does not itself establish permission for commercial use.
What FIBO-Edit does
Bria’s FIBO-Edit model on Replicate edits an image you supply. For example, Replicate’s listing uses the instruction “change lighting to starlight nighttime.” This is different from Bria’s separate FIBO text-to-image model, which creates images from text rather than editing a supplied image.
Bria describes FIBO-Edit as supporting broad changes—such as style, lighting, or atmosphere—as well as localized edits with a mask. These are documented capabilities, not a guarantee that every requested detail will be preserved or changed exactly as intended.
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How to make a first edit on Replicate
- Choose an image you have the right to use. Open the FIBO-Edit model page on Replicate and supply your source image through the hosted interface. The model can also be called through an API, but the steps and request lifecycle for Bria’s direct API are separate from Replicate’s.
- Write one clear instruction. State the change you want, such as “change the lighting to a starlit night.” Starting with one goal makes it easier to judge the output and adjust the request.
- Add a mask if the change should be local. Bria documents white mask regions as editable and black regions as preserved. The selected area is generated as replacement content; it is not simply a guaranteed pixel-perfect patch.
- Run the edit and inspect the result. Check both the changed area and surrounding details. If the output misses the goal, revise the instruction, mask, or other inputs and try again.
- Keep the inputs if you want to revisit a result. Save the source image and, if applicable, the mask, structured instruction, and seed used for the edit.
When to use a mask or a structured instruction
Use a mask for a regional change
A mask is useful when the desired change should be limited to part of the image—for example, replacing the background while intending to leave the subject untouched. In Bria’s documented convention, white marks the editable region and black marks the region to preserve. Because the masked area is regenerated, inspect edges and nearby details rather than assuming the boundary will be exact.
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Use structured JSON for explicit control
Replicate accepts either a text instruction or a JSON-formatted string in structured_instruction. The structured option is for workflows that need a more explicit representation of an edit or want to iterate from an existing structured instruction. Bria describes a vision-language-model bridge that converts ordinary instructions into structured JSON before FIBO-Edit renders the result; its direct API also allows structured instructions to be supplied or inspected.
For a first experiment, plain language is the simpler starting point. Use the structured field when your workflow needs that additional control, and follow the format expected by the interface you are using.
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Inputs and settings on Replicate
Replicate’s published schema lists these inputs. The schema describes the Replicate interface, not every constraint of Bria’s separate direct API.
| Input | Type or documented bounds | Purpose |
|---|---|---|
image |
File | The source image to edit. |
instruction |
Text | A natural-language description of the requested change; an alternative to structured_instruction. |
structured_instruction |
JSON-formatted string | An explicit structured edit description; an alternative to instruction. |
mask |
File | Optional mask for specifying an editable region. |
negative_prompt |
Text | An optional field for specifying what to avoid. |
seed |
Integer | A seed input for repeatability. |
guidance_scale |
Integer; schema bounds 3–5 | A model setting. The published schema gives the bounds but does not, in the cited description, establish one best value for every edit. |
| Output | Image URI | The generated image is returned as an image URI. |
Bria says reproducing a specific result depends on using the same source image, mask if used, structured instruction, and seed. Retaining those inputs improves the chance of recreating an edit, but it is not a promise of identical results across changes to a model or hosted service.
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How Replicate differs from Bria’s direct API
Bria’s direct /v2 image-editing API documents support for one to four reference images in supported requests. Its documentation says multi-reference editing does not support masking; masked requests are single-image requests. Those rules belong to Bria’s direct API and should not be assumed to describe Replicate’s interface.
Bria also documents its /v2 requests as asynchronous by default, returning a request ID and status URL, with sync: true available for simple, low-throughput requests. That describes Bria’s API, not Replicate’s request lifecycle. See Bria’s Image Editing API reference for its interface-specific details.
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Replicate price and commercial-use rights
Replicate displayed a price of $0.04 per output image for FIBO-Edit on October 7, 2026. This is the platform’s listed inference price at that time and can change. It is not a full project estimate or a commercial license fee.
Bria’s model README and Hugging Face model card identify the model weights as non-commercial under CC BY-NC 4.0. Bria links to a separate commercial licensing path, but the reviewed material does not state its price or detailed terms. If you plan to use the model for business purposes, review the applicable terms and obtain any commercial permission required from Bria. Paying Replicate’s inference charge should not be treated as commercial permission.
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Is FIBO-Edit a good fit?
- Consider it if you want to edit an existing image with a text instruction and may benefit from masking a local region.
- Consider another workflow if you need guaranteed preservation of every unmasked pixel, independently verified performance results, or a commercial-use grant that has not been confirmed for your situation.
- Choose the interface deliberately: Replicate-hosted inference, Bria’s direct API, and locally running model weights are distinct ways of accessing the model family, with different workflows and applicable terms.
The available documentation describes inputs and intended controls, but does not provide an independent benchmark establishing how reliably the model performs across images or edit types.
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