bfl/flux-differential-diffusion
Flux Differential Diffusion is BFL's intelligent image editing model. Transform, retouch, and reimagine existing images using text prompts - from background replacement to artistic style conversion.
PNG, JPEG, WebP, or GIF · 20 MiB maximum
Example output — click Run to generate your own
Send your first request
OpenAI-compatible endpoint with unified authentication and usage tracking.
https://api.sandbase.ai/v1/runbfl/flux-differential-diffusionInput Schema
7 parameters · 2 required · 5 optional
| Parameter | Type | Required | Description |
|---|---|---|---|
image | string | Required | URL of image to use as initial image. |
prompt | string | Required | The prompt to generate an image from. |
seed | integer | Optional | The same seed and the same prompt given to the same version of the model will output the same image every time. |
strength | number | Optional | The strength to use for image-to-image. 1.0 is completely remakes the image while 0.0 preserves the original. · Min: 0.01 · Max: 1 · Default: 0.85 |
guidance_scale | number | Optional | Min: 0 · Max: 20 · Default: 3.5 |
num_inference_steps | integer | Optional | Min: 1 · Max: 50 · Default: 28 |
change_map_image_url | string | Optional | URL of change map. |
Output Schema
| Field | Type | Description |
|---|---|---|
id | string | Unique identifier for the generation task |
status | string | Task status: pending, running, completed, failed, timeout |
model | string | Model used for the generation |
outputs | array | Array of output items |
outputs[].url | string | URL of the generated artifact |
outputs[].content_type | string | MIME type (e.g. image/png, video/mp4) |
error | object | null | Error details if failed, null on success |
error.type | string | Machine-readable error type code |
error.message | string | Human-readable error description |
Async Workflow
This model uses asynchronous execution. Submit a request and poll for the result.
- Submit — POST to /v1/run, receive an
id - Poll — GET /v1/run/{id} until status is
completed,failed, ortimeout - Retrieve — Read
outputsfrom the completed response
Code Examples
Ready-to-run snippets
# Step 1: Submit
curl -X POST https://api.sandbase.ai/v1/run \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "bfl/flux-differential-diffusion",
"image": "https://static.sandbase.ai/examples/bfl/flux-differential-diffusion/input_image_1.jpeg",
"prompt": "Tree of life under the sea, ethereal, glittering, lens flares, cinematic lighting, artwork by Anna Dittmann & Carne Griffiths, 8k, unreal engine 5, hightly detailed, intricate detailed.",
"strength": 0.85,
"guidance_scale": 3.5,
"num_inference_steps": 28,
"change_map_image_url": "https://static.sandbase.ai/examples/bfl/flux-differential-diffusion/input_change_map_image_url_0.jpeg"
}'
# Step 2: Poll result (replace <id>)
curl https://api.sandbase.ai/v1/run/<id> \
-H "Authorization: Bearer YOUR_API_KEY"API README
Flux Differential Diffusion
Flux Differential Diffusion belongs at the graduated revision across a single image stage of a visual workflow. Rather than treating the model as an isolated demonstration, teams can place it inside briefing, review, selection, and handoff practices where creative teams can plan a continuum between untouched and substantially changed areas instead of reducing every decision to a binary selection. This positioning clarifies why the model earns a place in a real creative pipeline and what kind of decision it helps people make.
A practical use of Flux Differential Diffusion is portrait retouching, atmosphere shifts, material changes, and localized art direction that should taper naturally into preserved content. Begin by agreeing on the creative objective and review criteria, prepare only the source material needed for that objective, and compare results against audience, brand, editorial, and production needs. Technical request choices remain documented below so the prose can stay focused on planning and creative value.
Highlights
Spatially varying edit strength. Allows strong regeneration in selected areas while other regions change only subtly.
Smooth transition zones. Blends different denoising intensities without hard visual seams between regions.
Fine-grained creative control. Supports nuanced retouching, emphasis, and localized restyling beyond a binary mask.
Context-preserving synthesis. Uses surrounding image information to keep altered regions visually integrated. This configuration emphasizes the model family's characteristic balance of prompt accuracy, visual detail, and creative flexibility.
Pricing
| Configuration | Billing unit | Price |
|---|---|---|
| Base generation | Per request | $0.05 |
When to Use
| ✅ Good fit | ❌ Consider alternatives |
|---|---|
| The project needs this exact FLUX capability | The intended task belongs to a different media workflow |
| Required source and control media are available | Necessary assets or usage rights are unavailable |
| Creative direction can state change and preservation goals | Output must be deterministic at pixel or frame level |
| Supported dimensions and formats match final delivery | Placement requires unsupported specifications |
| An asynchronous generated result fits production | A live frame-synchronous response is mandatory |
Prompt Guide
Lead with the main subject and action, then specify composition, context, lighting, materials, style, typography, and atmosphere. For editing, identify each source and clearly separate the requested transformation from the subjects, regions, geometry, or identity that must remain unchanged.
{
"guidance_scale": 3.5,
"image": "https://example.com/start-frame.png",
"prompt": "A cinematic, precisely composed result with a clear subject, controlled camera or viewpoint, realistic lighting, exact materials, and intentional atmosphere",
"seed": 1,
"strength": 0.85
}
Technical Specs
| Spec | Value |
|---|---|
| Model ID | bfl/flux-differential-diffusion |
| Input fields | seed (integer)<br>image (string)<br>prompt (string)<br>strength (number; 0.01–1)<br>guidance_scale (number; 0–20)<br>num_inference_steps (integer; 1–50)<br>change_map_image_url (string) |
| Required input | prompt, image |
| Output fields | url, content_type |
| Execution | Asynchronous job |
Related Models
bfl/flux-1.1/pro— Compare this concrete local family route.bfl/flux-1.1/pro-ultra— Compare this concrete local family route.bfl/flux-1.1/ultra/redux— Compare this concrete local family route.

