Flux Dev

Flux Dev

Playground

Try it on WaveSpeedAI!

FLUX.1 [dev] is a 12-billion-parameter rectified-flow transformer for text-to-image generation. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Generate high-quality images with FLUX.1 [dev], a versatile and powerful image generation model. Whether you need text-to-image creation, image-to-image transformation, or precise inpainting — this model delivers stunning results with exceptional detail and prompt adherence.

Why It Stands Out

  • Multi-mode generation: Supports text-to-image, image-to-image, and inpainting workflows in one model.
  • High resolution output: Generate images up to 1024×1024 with sharp detail and clarity.
  • Prompt Enhancer: Built-in AI-powered prompt optimization for better results.
  • Flexible aspect ratios: Customize width and height independently for any format.
  • Batch generation: Create multiple images in a single request.
  • Reproducibility: Use the seed parameter to recreate exact results or explore variations.
  • Multiple output formats: Export as JPEG or PNG based on your needs.

Pricing

OutputPrice
Per image$0.012

Total cost = $0.012 × num_images

Parameters

ParameterRequiredDescription
promptYesText description of the image you want to generate.
imageNoSource image for image-to-image or inpainting mode.
mask_imageNoMask image for inpainting (white areas will be regenerated).
strengthNoHow much to transform the source image (0.0–1.0, default: 0.8).
widthNoOutput width in pixels (default: 1024).
heightNoOutput height in pixels (default: 1024).
num_inference_stepsNoQuality/speed trade-off (default: 28).
seedNoSet for reproducibility; -1 for random.
guidance_scaleNoPrompt adherence strength (default: 3.5).
num_imagesNoNumber of images to generate (default: 1).
output_formatNoOutput format: jpeg or png (default: jpeg).
enable_base64_outputNoReturn base64 string instead of URL (API only).
enable_sync_modeNoWait for result before returning response (API only).

How to Use

Text-to-Image:

  1. Write a prompt describing the image you want. Use the Prompt Enhancer for AI-assisted optimization.
  2. Set width and height for your desired aspect ratio.
  3. Adjust guidance_scale and num_inference_steps as needed.
  4. Click Run and download your image.

Image-to-Image:

  1. Upload a source image.
  2. Write a prompt describing the transformation you want.
  3. Adjust the strength parameter — higher values allow more dramatic changes.
  4. Click Run and download your image.

Inpainting:

  1. Upload a source image and a mask image.
  2. White areas in the mask will be regenerated based on your prompt.
  3. Write a prompt describing what should appear in the masked region.
  4. Click Run and download your image.

Best Use Cases

  • Creative Art & Illustration — Generate unique artwork, concept art, and digital illustrations.
  • Product Visualization — Create product mockups and lifestyle imagery.
  • Marketing & Social Media — Produce eye-catching visuals for campaigns and posts.
  • Photo Editing & Enhancement — Transform or repair images with inpainting.
  • Design Prototyping — Quickly visualize ideas before committing to full production.

Pro Tips for Best Quality

  • Be descriptive in your prompt — include style, mood, lighting, composition, and specific details.
  • For image-to-image, use lower strength (0.3–0.5) to preserve more of the original, higher (0.7–0.9) for dramatic changes.
  • Use inpainting with precise masks for seamless object removal or replacement.
  • Fix the seed when iterating to compare the effect of different parameters.
  • Generate multiple images (num_images > 1) to explore variations quickly.

Notes

  • If using image URLs, ensure they are publicly accessible.
  • Processing time varies based on resolution and current queue load.
  • Please ensure your prompts comply with content guidelines.

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",
  "strength": 0.8,
  "size": "1024*1024",
  "num_inference_steps": 28,
  "seed": -1,
  "guidance_scale": 3.5,
  "num_images": 1,
  "output_format": "jpeg"
}
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-dev" \
  -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.
imagestringNo-The image to generate an image from.
mask_imagestringNo-The mask image tells the model where to generate new pixels (white) and where to preserve the original image (black). It acts as a stencil or guide for targeted image editing.
strengthnumberNo0.80 ~ 1Strength indicates extent to transform the reference image.
sizestringNo1024*1024-The size of the generated media in pixels (width*height).
num_inference_stepsintegerNo281 ~ 50The number of inference steps to perform.
seedintegerNo-1-The random seed to use for the generation. -1 means a random seed will be used.
guidance_scalenumberNo3.51 ~ 20The guidance scale to use for the generation.
num_imagesintegerNo11 ~ 4The number of images to generate.
output_formatstringNojpegjpeg, png, webpThe format of the output image.
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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