Experimental FLUX.1 Kontext [pro] with multi-image handling to combine context from multiple images for richer output. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Bezczynny

$0.04za uruchomienie·~25 / $1

The boy is holding a gun in his hand.

A girl with a hat and sunglasses is in the garden.

The clown stands in front of the house.

Little girl holding flowers in her hands.

The girl is wearing a hippocampus brooch.

The boy put on sunglasses.

The girl puts on sunglasses.

The horse is carrying fruits.

The girl happily hugs the doll.

Santa Claus is standing in front of the tree.

A boy wears a chain around his neck.
FLUX Kontext Pro Multi is a fast, reliable multi-image model for context-guided generation and editing. Provide a text prompt plus up to 5 reference images, and the model uses them to improve identity consistency, style alignment, and scene coherence—ideal for practical production workflows that need strong control at a lower cost.
$0.04 per image.
Total cost = num_images × $0.04 Example: num_images = 4 → $0.16
Input:
Output:
Assign roles to references to reduce ambiguity:
Template: Use image 1 for identity. Use image 2 for outfit/material. Use image 3 for style. Use image 4 for lighting. Use image 5 for background/scene. Generate the shot described below. Keep the key traits unchanged.
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-kontext-pro/multi 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 Pro Multi below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-kontext-pro/multi" \
-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": 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].// 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-pro/multi", {
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"seed": 0,
"guidance_scale": 3.5,
"aspect_ratio": "21:9",
"enable_sync_mode": false
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"wavespeed-ai/flux-kontext-pro/multi",
{
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"seed": 0,
"guidance_scale": 3.5,
"aspect_ratio": "21:9",
"enable_sync_mode": false
}
)
print(output["outputs"][0]) # → URL of the generated outputFlux Kontext Pro Multi is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. Experimental FLUX.1 Kontext [pro] with multi-image handling to combine context from multiple images for richer output. 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-kontext-pro-multi.
Flux Kontext Pro Multi starts at $0.040 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`, `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-pro-multi.
Average end-to-end generation time on WaveSpeedAI is around 17 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.