Flux Kontext Max | Fast Image Editing API

FLUX Kontext Max (Image-to-Image Editing) — wavespeed-ai/flux-kontext-max

FLUX Kontext Max is a premium image-to-image editing model built for high-fidelity, instruction-following transformations. Provide a source image plus a natural-language edit prompt, and it performs precise local or global edits while maintaining strong visual coherence—ideal for demanding creative direction, high-end retouching, and style-driven transformations.

Key capabilities

High-fidelity instruction-based image editing from a single input image
Strong prompt adherence for complex, multi-constraint edits
Handles both local edits (specific elements) and global edits (overall look)
Excellent for style transformations (e.g., toy style, clay, illustration) while preserving composition

Typical use cases

Premium retouching: lighting correction, cleanup, detail enhancement
Background swaps with consistent lighting/shadows
Product and branding edits requiring high accuracy
Style transformations with minimal drift (toy, clay, cinematic, illustration)
Creative iterations where output quality matters more than speed

Pricing

$0.08 per image.

Inputs and outputs

Input:

image (required): Source image (upload or public URL)
prompt (required): Edit instruction

Output:

One or more edited images (controlled by num_images, if available in your interface)

Parameters

prompt (required): Edit instruction describing what to change and what to preserve
image (required): Source image
seed: Fixed value for reproducibility; leave empty/random for variation
guidance_scale: Prompt adherence strength (higher = stricter; too high may over-edit)
aspect_ratio: Output aspect ratio (choose to control framing/cropping)

Prompting guide

For best control, use a “preserve + edit + constraints” structure:

Template: Keep [what must stay]. Change [what to edit]. Ensure [constraints]. Match [lighting/shadows/perspective].

Example prompts

Keep the person’s face, pose, and clothing unchanged. Convert the entire image to a high-quality toy style with realistic plastic texture, soft studio lighting, and clean highlights. Keep the background composition consistent.
Keep the subject identity and expression unchanged. Replace the background with a clean pastel studio backdrop. Match lighting direction and shadow softness.
Remove background clutter and keep the main subject sharp. Apply a gentle cinematic color grade without changing composition.

Best practices

Start with one change per run, then iterate for precision.
If the edit is too strong, lower guidance_scale and add a clearer preserve clause.
Fix seed for stable comparisons across prompt variants.
Choose aspect_ratio intentionally to avoid unexpected cropping.

Flux Kontext Max API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-kontext-max 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 Kontext Max below.

HTTP example

# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-kontext-max" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d '{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "image": "https://example.com/your-input.jpg",
    "seed": 0,
    "guidance_scale": 3.5,
    "aspect_ratio": "21:9",
    "enable_sync_mode": 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].

Node.js example

// 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-kontext-max", {
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "image": "https://example.com/your-input.jpg",
        "seed": 0,
        "guidance_scale": 3.5,
        "aspect_ratio": "21:9",
        "enable_sync_mode": false
});

console.log(result.outputs[0]); // → URL of the generated output

Python example

# pip install wavespeed
import wavespeed

output = wavespeed.run(
    "wavespeed-ai/flux-kontext-max",
    {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "image": "https://example.com/your-input.jpg",
    "seed": 0,
    "guidance_scale": 3.5,
    "aspect_ratio": "21:9",
    "enable_sync_mode": false
}
)

print(output["outputs"][0])  # → URL of the generated output

Flux Kontext Max API — Frequently asked questions

What is the Flux Kontext Max API?

Flux Kontext Max is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. FLUX.1 Kontext [max] boosts prompt adherence and typography generation for consistent, high-quality image editing at speed. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Flux Kontext Max API?

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-kontext-max.

How much does Flux Kontext Max cost per run?

Flux Kontext Max starts at $0.080 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.

What inputs does Flux Kontext Max accept?

Key inputs: `prompt`, `image`, `aspect_ratio`, `seed`, `guidance_scale`, `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-kontext-max.

How long does Flux Kontext Max take to generate?

Average end-to-end generation time on WaveSpeedAI is around 29 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.

Can I use Flux Kontext Max outputs commercially?

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.

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