Flux Dev Ultra Fast
Flux-dev text to image model, 12 billion parameter rectified flow transformer, ultra fast!
Features
flux-dev-ultra-fast is a 12 billion parameter rectified flow transformer capable of generating images from textual descriptions.
Key Features
- Ultra-Fast Generation: Delivers high-quality images from text prompts in under 2 seconds.
- High-Quality Image Generation: Produces detailed and visually appealing images from textual prompts.
- 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.
ComfyUI
flux-dev-ultra-fast is also available on ComfyUI, providing local inference capabilities through a node-based workflow, ensuring flexible and efficient image generation on your system.
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.wavespeed.ai/api/v2/wavespeed-ai/flux-dev-ultra-fast" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"prompt": "A young, attractive Indian couple standing side by side at their traditional wedding ceremony, both facing the camera with warm smiles. The bride wears a red and gold lehenga with intricate embroidery, heavy jewelry, and a maang tikka; the groom in an ivory sherwani with a red stole and turban. Background: lavish wedding decor with marigold flowers and fairy lights. Rich colors, sharp focus, photorealistic, cinematic lighting, full-body portrait, authentic Indian wedding atmosphere.",
"strength": 0.8,
"size": "1024*1024",
"num_inference_steps": 28,
"seed": -1,
"guidance_scale": 3.5,
"num_images": 1,
"enable_base64_output": true,
"enable_safety_checker": true
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v2/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
Parameter | Type | Required | Default | Range | Description |
---|---|---|---|---|---|
prompt | string | Yes | A young, attractive Indian couple standing side by side at their traditional wedding ceremony, both facing the camera with warm smiles. The bride wears a red and gold lehenga with intricate embroidery, heavy jewelry, and a maang tikka; the groom in an ivory sherwani with a red stole and turban. Background: lavish wedding decor with marigold flowers and fairy lights. Rich colors, sharp focus, photorealistic, cinematic lighting, full-body portrait, authentic Indian wedding atmosphere. | - | 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 | 0.0 ~ 1.0 | 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 ~ 20 | 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 | true | - | If set to true, the output base64 will be enabled. |
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
Result Request 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 |