Flux 2 Turbo Edit

Flux 2 Turbo Edit

Playground

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

Features

FLUX 2 Turbo Edit (wavespeed-ai/flux-2-turbo/edit) is a fast, practical image-to-image editing model for applying natural-language changes to an existing image (for example: lighting, color, props, background, or style), while keeping the original composition and identity cues stable.

It’s well suited for high-volume creative workflows where you want reliable edits with minimal configuration—provide an input image, describe the change, and iterate quickly.


Key capabilities

  • Prompt-guided image editing (image-to-image) Apply targeted edits using plain-language instructions (for example: “make it winter”, “change the background to studio gray”, “increase contrast while keeping the face and pose”).

  • Composition- and identity-preserving updates Optimized for “update, not regenerate” workflows, helping preserve layout, subjects, and overall visual identity across edits.

  • Repeatable results via seed control Use a fixed seed to reproduce the same edit or generate controlled variations for testing and comparison.

  • Flexible image inputs (up to 4 images) Supports 1–4 input images, allowing reference-based edits or multi-image context.

  • Production-friendly outputs Results can be returned as hosted image URLs by default, or as Base64-encoded data for direct embedding.


Parameters and how to use

  • prompt: (required) The edit instruction describing what you want to change.
  • images: (required) Array of input image URLs (1–3 items) to edit.
  • size: Output size in pixels as "width*height".
  • seed: Random seed for generation (-1 for random; fixed integer for repeatability).
  • enable_sync_mode: If true, waits for completion and returns the result in the response (API only).
  • enable_base64_output: If true, returns Base64-encoded output instead of a URL (API only).

Prompt

Write your prompt like a concise edit brief:

  1. State the change clearly Example: “Change the weather to winter. Add light snowfall and frosty breath.”
  2. Explicitly say what must stay the same Example: “Keep the same person, pose, face, and camera framing.”
  3. Specify visual attributes Mention lighting, materials, mood, or style (for example: “soft studio lighting”, “high-contrast cinematic look”).
  4. Use exact values for precision For branding or color accuracy, specify exact values such as hex color codes.

Media (Images)

  • Provide images as publicly accessible image URLs.
  • Supports 1 to 4 images per request.

Other parameters

  • size Controls output resolution using "width*height". Typical values:

  • "1024*1024" for square assets

  • "1536*1024" for wide banners

  • "1024*1536" for portrait layouts

  • seed

  • -1 for a new variation each run

  • A fixed integer (for example: 12345) for repeatable edits

  • enable_sync_mode (API only) Set to true if you want the API call to block until the result is ready.

  • enable_base64_output (API only) Set to `true if you need Base64 output instead of a hosted image URL.

After you finish configuring the parameters, click Run, preview the result, and iterate if needed.


Pricing

$0.019 per run


Notes

  • For the most stable results, make one type of change at a time and reuse the same seed while iterating.
  • If edits change too much of the original image, reinforce constraints in the prompt (for example: “keep the same composition, identity, and proportions”).

  • FLUX.2 Dev Edit – A lightweight, cost-efficient FLUX.2 editing variant.
  • FLUX.2 Flex Edit – A more flexible option for creative and stylistic exploration.
  • FLUX.2 Pro Edit – Higher-fidelity edits designed for production and brand assets.
  • FLUX.2 Max Edit – The highest-quality FLUX.2 editing model for detail-critical work.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "images": [
    "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
  ],
  "seed": -1
}
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-2-turbo/edit" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(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' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  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

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
promptstringYes-The positive prompt for the generation.
imagesarray<string>Yes-0 ~ 4 itemsList of URLs of input images for editing. The maximum number of images is 4.
seedintegerNo-1-The random seed to use for the generation. -1 means a random seed will be used.
enable_base64_outputbooleanNofalse-If set to `true`, the prediction's `output` strings are returned as **naked base64** (no `data:<mime>;base64,` prefix). When `false` (default), outputs are returned as URLs pointing to our CDN.
enable_sync_modebooleanNofalse-If set to `true`, the request attempts to wait for the generated result and return outputs in the same response. If the result is not ready within the sync wait window, the API can return a timeout body while the task continues processing. This option is only available via the API and is supported only by some models.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayOutput values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction
data.modelstringModel ID used for the prediction
data.outputsarray<string | object>Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model.
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to poll for the prediction result
data.statusstringStatus: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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