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Flux Kontext Pro

wavespeed-ai /

FLUX.1 Kontext [pro] offers improved prompt adherence and accurate typography generation for consistent, high-quality edits at speed. Ready-to-use REST API, best performance, no coldstarts, affordable pricing.

image-to-image
Input

Idle

A woman is brewing tea

$0.04per run·~25 / $1

Next:

ExamplesView all

A woman is brewing tea

A woman is brewing tea

Enveloped by the deep mountains and old forests

Enveloped by the deep mountains and old forests

Add sunglasses for boys

Add sunglasses for boys

A vibrant image of Monkey D. Luffy standing confidently on the wooden deck of a pirate ship under a sunny sky with seagulls flying overhead.

A vibrant image of Monkey D. Luffy standing confidently on the wooden deck of a pirate ship under a sunny sky with seagulls flying overhead.

Switch to pixel art style

Switch to pixel art style

A white unicorn with a rainbow mane and tail rearing up in a magical forest with glowing plants and sparkling dust motes, soft dappled light.

A white unicorn with a rainbow mane and tail rearing up in a magical forest with glowing plants and sparkling dust motes, soft dappled light.

Change background to grassland, anime style

Change background to grassland, anime style

Color the dolphin

Color the dolphin

An old man is writing

An old man is writing

Santa Claus in front of the Christmas tree.

Santa Claus in front of the Christmas tree.

The girl opens her eyes and smiles at the camera.

The girl opens her eyes and smiles at the camera.

A man eating noddles

A man eating noddles

A man eating noddles

A man eating noddles

Convert the text on the girl's clothes to "WaveSpeedAI"

Convert the text on the girl's clothes to "WaveSpeedAI"

reimagine the scene as a traditional Chinese ink painting, convert the young man’s outfit to ancient hanfu while keeping facial features intact, replace urban background with misty mountains and willow trees, apply desaturated ink wash style

reimagine the scene as a traditional Chinese ink painting, convert the young man’s outfit to ancient hanfu while keeping facial features intact, replace urban background with misty mountains and willow trees, apply desaturated ink wash style

convert to high fashion editorial style, add dramatic shadows and high contrast lighting, replace white wall with abstract textured backdrop, enhance makeup with bold colors, keep outfit but stylize pose and expression for a Vogue magazine look

convert to high fashion editorial style, add dramatic shadows and high contrast lighting, replace white wall with abstract textured backdrop, enhance makeup with bold colors, keep outfit but stylize pose and expression for a Vogue magazine look

a man in his 30s standing on a busy modern street, wearing a black leather jacket and jeans, background of glass buildings and cars, daytime, candid photography style

a man in his 30s standing on a busy modern street, wearing a black leather jacket and jeans, background of glass buildings and cars, daytime, candid photography style

transform the scene into an impressionist oil painting style, enhance brushstroke textures and warm color palette, maintain the woman’s pose and outfit, change lighting to soft golden hour, add painterly indoor background with vintage furniture

transform the scene into an impressionist oil painting style, enhance brushstroke textures and warm color palette, maintain the woman’s pose and outfit, change lighting to soft golden hour, add painterly indoor background with vintage furniture

Related Models

README

FLUX.1 Kontext [pro]

FLUX.1 Kontext [pro] is a 12 billion parameter rectified flow transformer capable of editing images based on text instructions.

Key Features

  1. Change existing images based on an edit instruction.
  2. Have character, style and object reference without any finetuning.
  3. Robust consistency allows users to refine an image through multiple successive edits with minimal visual drift.
Note:This website uses AI models provided by third parties.

Flux Kontext Pro API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-kontext-pro with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Flux Kontext Pro below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "guidance_scale": 3.5,
    "aspect_ratio": "21:9"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-kontext-pro" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $WAVESPEED_API_KEY" \
  -d "$REQUEST_BODY")

TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
  RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi

# 2. Poll until the prediction finishes.
while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
    -H "Authorization: Bearer $WAVESPEED_API_KEY")
  RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
  STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
  case "$STATUS" in
    completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
    failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
    created|processing) sleep 2 ;;
    *) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
  esac
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-kontext-pro";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');

async function requestJson(url, options = {}) {
  const response = await fetch(url, options);
  if (!response.ok) throw new Error(await response.text());
  return response.json();
}

// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
        "guidance_scale": 3.5,
        "aspect_ratio": "21:9"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;

// 2. Poll until the prediction finishes.
while (true) {
  const resultBody = await requestJson(resultUrl, {
    headers: { "Authorization": `Bearer ${apiKey}` },
  });
  const result = resultBody.data ?? resultBody;
  if (result.status === "completed") {
    console.log(result.outputs);
    break;
  }
  if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
  if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
  await new Promise(resolve => setTimeout(resolve, 2000));
}
Python example
import json
import os
import time
from urllib.request import Request, urlopen

api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
    "guidance_scale": 3.5,
    "aspect_ratio": "21:9"
}

def request_json(url, data=None):
    request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
    with urlopen(request) as response:
        return json.load(response)

# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-kontext-pro", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
    raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"

# 2. Poll until the prediction finishes.
while True:
    result_body = request_json(result_url)
    result = result_body.get("data", result_body)
    status = result.get("status")
    if status == "completed":
        print(result.get("outputs", []))
        break
    if status in {"failed", "cancelled", "timeout"}:
        raise RuntimeError(result)
    if status not in {"created", "processing"}:
        raise RuntimeError(f"Unexpected status: {status}")
    time.sleep(2)

Flux Kontext Pro API — Frequently asked questions

What is the Flux Kontext Pro API?

Flux Kontext Pro is a WaveSpeedAI model for image editing, exposed as a REST API on WaveSpeedAI. FLUX.1 Kontext [pro] offers improved prompt adherence and accurate typography generation for consistent, high-quality edits at speed. Ready-to-use REST 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 Pro 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 result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/wavespeed-ai/flux-kontext-pro.

How much does Flux Kontext Pro cost per run?

Flux Kontext Pro 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.

What inputs does Flux Kontext Pro accept?

Key inputs: `prompt`, `image`, `aspect_ratio`, `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.

How long does Flux Kontext Pro take to generate?

Median end-to-end generation time on WaveSpeedAI is around 13 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Flux Kontext Pro 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.