Flux 2 Dev Edit API Documentation

Flux 2 Dev Edit API Documentation

Playground

Try it on WaveSpeedAI!

FLUX.2 [dev] Edit enables 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.

Features

FLUX.2 [dev] Edit is the lean editing companion to FLUX.2 [dev] Text-to-Image: a lightweight, open-source model that updates existing images quickly while keeping their core look intact. It is built for day-to-day production tasks where you need reliable edits at scale without burning GPU budget.


Built for

  • Quick visual tweaks to existing assets
  • Consistent updates to product, UI, or brand imagery
  • High-volume editing in cost-sensitive pipelines
  • Workflows already using FLUX.2 [dev] for generation
  • LoRA-based domain or brand customisation on a small footprint

Lean editing engine for everyday pipelines

Instead of regenerating images from scratch, FLUX.2 [dev] Edit focuses on local changes. You feed it an image plus an edit prompt (and, when supported, a mask or strength setting); it modifies only the requested areas, keeping layout, characters, and overall style stable so assets remain recognisable across versions.


Key benefits

• Prompt-guided adjustments

Change lighting, colour, clothing, props, or background details with short text instructions, replacing manual retouching and pixel-level editing.

• Consistent look and feel

Refresh campaigns, seasonal variants, or A/B test creatives while preserving character identity, composition, and brand language across all outputs.

• Open and integration-friendly

Built on the same open FLUX.2 stack, making it straightforward to plug into internal tools, debug behaviour, or extend with custom logic.

• Small, efficient footprint

The compact dev architecture keeps inference costs low, which is ideal for batch processing, automation, and always-on backend services.

• Flexible I/O

Accepts standard image formats and returns JPEG or PNG, so edited results fit directly into web, design, and post-production workflows.

• Repeatable results

Seed control plus fixed prompts make it easy to recreate previous edits or generate controlled variations for QA, experimentation, and asset refreshes.


Pricing

Simple per-image billing:

  • $0.024 per edited image

FLUX.2 family on WaveSpeedAI

Combine FLUX.2 [dev] Edit with the rest of the FLUX.2 lineup for a full generate-and-refine workflow:


More Image Tools on WaveSpeedAI

  • Nano Banana Pro – Google’s Gemini-based text-to-image model for sharp, coherent, prompt-faithful visuals that work great for ads, keyframes, and product shots.
  • Seedream V4 – ’s style-consistent, multi-image generator ideal for posters, campaigns, and large batches of on-brand illustrations.
  • Qwen Edit Plus – an enhanced Qwen-based image editor for precise inpainting, cleanup, and local style changes while preserving overall composition.

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"
  ]
}
JSON
)

# 1. Submit the prediction once. Never retry this request automatically:
# a retry after an unclear failure can create a second, billed task.
CHECK='The task may already exist. Check History or the predictions list before submitting again.'
if ! SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  --connect-timeout 10 --max-time 60 \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-2-dev/edit" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}"); then
  printf 'Submit failed. %s\n' "${CHECK}" >&2
  exit 1
fi

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 "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id. %s\n' "${CHECK}" >&2
  exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"

# 2. Poll until the prediction reaches a final status.
BODY_FILE=$(mktemp)
trap 'rm -f "${BODY_FILE}"' EXIT
while true; do
  # Transient errors (429, 5xx) are retried, honoring Retry-After.
  HTTP_CODE=$(curl --silent --show-error --fail-with-body \
    --connect-timeout 10 --max-time 60 --retry 5 --retry-delay 2 \
    --output "${BODY_FILE}" --write-out '%{http_code}' \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}" || true)
  case "${HTTP_CODE}" in
    2??) ;;
    000|429|5??)  # dropped connection or temporary error: keep polling
      printf 'Task %s: HTTP %s, polling again in 10s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
      sleep 10; continue ;;
    *) printf 'Task %s: HTTP %s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
      cat "${BODY_FILE}" >&2; exit 1 ;;
  esac
  RESULT=$(jq 'if type == "object" and has("data") then .data else . end' "${BODY_FILE}")
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted)
      printf 'Task %s ended with status %s\n' "${PREDICTION_ID}" "${STATUS}" >&2
      printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done

Retry temporary errors only while polling, never the submit request. Errors, retries and timeouts

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
promptstringYes-The positive prompt for the generation.
imagesarray<string>Yes-0 ~ 3 itemsList of URLs of input images for editing. The maximum number of images is 3.
sizestringNo-256 ~ 2048Advanced option. The size of the generated media in pixels (width*height).
seedintegerNo--The random seed to use for the generation. -1 means a random seed will be used.

Every model also accepts the global request options enable_sync_mode and enable_base64_output; see their pages for details.

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.statusstringTask status. completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses.
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.statusstringStatus: completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses
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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