FLUX.2 [flex] Edit delivers precise image-to-image editing from Black Forest Labs—apply natural-language instructions and exact hex color control for consistent, studio-quality results. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Boşta

$0.12çalıştırma başına·~83 / $10





FLUX.2 [flex] Edit is a configurable image editing model built on FLUX.2 [flex], aimed at teams that need fine control over how edits are applied. It can work with one or multiple reference images and lets you tune quality–speed trade-offs, making it a good fit for style-heavy, budget-conscious production workflows.
Multi-image product and lifestyle compositions
Brand asset refinement with style or reference images
Typography and layout touch-ups in existing designs
E-commerce and marketing visuals that need frequent updates
• Multi-image aware composition
Combine several reference images in a single edit when building product collages or style transfers. You can point to specific references by index (for example, “use the background from image 2 and the typography from image 4”) or simply describe them in the prompt.
• Adjustable quality and speed
Control inference steps based on how complex the edit is: quick colour swaps or minor clean-up can run with fewer steps, while dense multi-image edits can use higher settings for extra detail.
• Guidance control for edits
Decide how strictly the model should follow your instructions versus preserving the original look. Dial guidance lower for looser, creative reinterpretations; raise it when you want near-literal edits.
• Strong text and layout handling
Well suited for fixing signage, labels, and UI text inside images, keeping typography sharp while updating wording, colours, or layout.
• Natural language plus hex colour control
Describe edits in plain language (“make the jacket match the blue from our brand palette”) and use hex codes when you need exact corporate colours for products, UI elements, or backgrounds.
• LoRA- and pipeline-friendly
Works smoothly with LoRA adapters for brand or domain-specific styles, and its configurable nature makes it easy to slot into larger editing pipelines that need both flexibility and cost control.
• Output ready for production
Exports JPEG so edited assets can go straight into design tools, websites, or print-oriented workflows without extra conversion.
Simple per-image billing:
Mix and match FLUX.2 models for a full generate-and-edit workflow:
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-2-flex/edit with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Flux 2 Flex Edit below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-2-flex/edit" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"seed": -1,
"enable_sync_mode": false,
"enable_base64_output": false
}'
# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# When status is "completed", read the output from data.outputs[0].// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("wavespeed-ai/flux-2-flex/edit", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"seed": -1,
"enable_sync_mode": false,
"enable_base64_output": false
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"wavespeed-ai/flux-2-flex/edit",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"seed": -1,
"enable_sync_mode": false,
"enable_base64_output": false
}
)
print(output["outputs"][0]) # → URL of the generated outputFlux 2 Flex Edit is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. FLUX.2 [flex] Edit delivers precise image-to-image editing from Black Forest Labs—apply natural-language instructions and exact hex color control for consistent, studio-quality results. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/flux-2-flex-edit.
Flux 2 Flex Edit starts at $0.12 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `prompt`, `images`, `seed`, `enable_base64_output`, `enable_sync_mode`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/wavespeed-ai/flux-2-flex-edit.
Average end-to-end generation time on WaveSpeedAI is around 58 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (WaveSpeedAI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.