Flux Dev

Flux-dev text to image model, 12 billion parameter rectified flow transformer

Features

flux-dev is a 12 billion parameter rectified flow transformer capable of generating images from textual descriptions.

Key Features

High-Quality Image Generation: Produces detailed and visually appealing images from textual prompts.
Efficient Training with Guidance Distillation: Utilizes guidance distillation techniques to enhance training efficiency and model responsiveness.
Open Weights: Provides open access to model weights, facilitating scientific research and creative development.
Versatile Usage: Suitable for personal, scientific, and commercial applications, offering flexibility across various use cases.

Limitations

Creative Focus: Designed primarily for creative image synthesis; not intended for generating factually accurate content.
Inherent Biases: Outputs may reflect biases present in the training data.
Input Sensitivity: The quality and consistency of generated images depend significantly on the quality of the input text; subtle variations may lead to output variability.
Prompt Dependency: The model's performance is closely tied to the clarity and structure of the prompts; careful crafting may be necessary for optimal results.

Out-of-Scope Use

The model and its derivatives may not be used in any way that violates applicable national, federal, state, local, or international law or regulation, including but not limited to:

Exploiting, harming, or attempting to exploit or harm minors, including solicitation, creation, acquisition, or dissemination of child exploitative content.
Generating or disseminating verifiably false information with the intent to harm others.
Creating or distributing personal identifiable information that could be used to harm an individual.
Harassing, abusing, threatening, stalking, or bullying individuals or groups.
Producing non-consensual nudity or illegal pornographic content.
Making fully automated decisions that adversely affect an individual’s legal rights or create binding obligations.
Facilitating large-scale disinformation campaigns.

Accelerated Inference

Our accelerated inference approach leverages advanced optimization technology from WavespeedAI. This innovative fusion technique significantly reduces computational overhead and latency, enabling rapid image generation without compromising quality. The entire system is designed to efficiently handle large-scale inference tasks while ensuring that real-time applications achieve an optimal balance between speed and accuracy. For further details, please refer to the blog post.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

Submit the task

curl --location --request POST "https://api.muapi.ai/api/v1/flux-dev-image" \
--header "Content-Type: application/json" \
--header "x-api-key: ${MUAPIAPP_API_KEY}" \
--data-raw '{
    "prompt": "A stylish model, fashion show, showcase a designer outfit, orange colour suit, conspicuous jewelry, fashion show background, vibrant color, dramatic makeup",
    "image": "",
    "size": "1024*1024",
    "num_inference_steps": 28,
    "seed": -1,
    "guidance_scale": 3.5,
    "num_images": 1
}'

Get the result

curl --location --request GET "https://api.muapi.ai/api/v1/predictions/${requestId}/result" \
--header "x-api-key: ${MUAPIAPP_API_KEY}"

Task Submission Parameters

Parameter	Type	Required	Default	Range	Description
prompt	string	Yes	A stylish model, fashion show, showcase a designer outfit, orange colour suit, conspicuous jewelry, fashion show background, vibrant color, dramatic makeup	-	The prompt to generate an image from.
image	string	No	-	-	The image to generate an image from.
mask_image	string	No	-	-	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.
strength	number	No	0.8	0.00 ~ 1.00	Strength indicates extent to transform the reference image
size	string	No	1024*1024	512 ~ 1536 per dimension	The size of the generated image.
num_inference_steps	integer	No	28	1 ~ 50	The number of inference steps to perform.
seed	integer	No	-1	-1 ~ 9999999999	The same seed and the same prompt given to the same version of the model will output the same image every time.
guidance_scale	number	No	3.5	1.0 ~ 20.0	The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you.
num_images	integer	No	1	1 ~ 4	The number of images to generate.
enable_base64_output	boolean	No	false	-	If enabled, the output will be encoded into a BASE64 string instead of a URL.
enable_safety_checker	boolean	No	true	-	If set to true, the safety checker will be enabled.

Parameters

Task Submission Parameters

Parameter	Type	Required	Default	Range/Example	Description
prompt	string	Yes	-	-	The prompt to generate an image from.
image	string	No	-	-	The image to generate an image from.
mask_image	string	No	-	-	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.
strength	number	No	0.8	0.00 ~ 1.00	Strength indicates extent to transform the reference image
size	string	No	1024*1024	512 ~ 1536 per dimension	The size of the generated image.
num_inference_steps	integer	No	28	1 ~ 50	The number of inference steps to perform.
seed	integer	No	-1	-1 ~ 9999999999	The same seed and the same prompt given to the same version of the model will output the same image every time.
guidance_scale	number	No	3.5	1.0 ~ 20.0	The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you.
num_images	integer	No	1	1 ~ 4	The number of images to generate.
enable_base64_output	boolean	No	false	-	If enabled, the output will be encoded into a BASE64 string instead of a URL.
enable_safety_checker	boolean	No	true	-	If set to true, the safety checker will be enabled.

Response Parameters

Parameter	Type	Description
code	integer	HTTP status code (e.g., 200 for success)
message	string	Status message (e.g., “success”)
data.id	string	Unique identifier for the prediction, Task Id
data.model	string	Model ID used for the prediction
data.outputs	array	Array of URLs to the generated content (empty when status is not completed)
data.urls	object	Object containing related API endpoints
data.urls.get	string	URL to retrieve the prediction result
data.has_nsfw_contents	array	Array of boolean values indicating NSFW detection for each output
data.status	string	Status of the task: created, processing, completed, or failed
data.created_at	string	ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.error	string	Error message (empty if no error occurred)
data.timings	object	Object containing timing details
data.timings.inference	integer	Inference time in milliseconds

Result Query Parameters

Parameter	Type	Required	Default	Description
id	string	Yes	-	Task ID

Result Response Parameters

Parameter	Type	Description
code	integer	HTTP status code (e.g., 200 for success)
message	string	Status message (e.g., “success”)
data	object	The prediction data object containing all details
data.id	string	Unique identifier for the prediction
data.model	string	Model ID used for the prediction
data.outputs	array	Array of URLs to the generated content (empty when status is not completed)
data.urls	object	Object containing related API endpoints
data.urls.get	string	URL to retrieve the prediction result
data.has_nsfw_contents	array	Array of boolean values indicating NSFW detection for each output
data.status	string	Status of the task: created, processing, completed, or failed
data.created_at	string	ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.error	string	Error message (empty if no error occurred)
data.timings	object	Object containing timing details
data.timings.inference	integer	Inference time in milliseconds