Overview

Description:

FLUX.1-schnell is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions at fast speeds. Trained using latent adversarial diffusion distillation, FLUX.1-schnell can generate high-quality images in only 1 to 4 steps.

This model is ready for commercial use.

Third-Party Community Consideration:

This model is not owned or developed by NVIDIA. This model has been developed and built to a third-party’s requirements for this application and use case; see link to:

• black-forest-labs/FLUX.1-schnell Model Card

Terms of use

GOVERNING TERMS: The trial service is governed by the NVIDIA API Trial Terms of Service. The Flux.1 Schnell model is available at https://huggingface.co/black-forest-labs/FLUX.1-schnell. Use of the NVIDIA Cosmos-1.0 Guardrail is governed by the NVIDIA Open Model License Agreement. ADDITIONAL INFORMATION: Llama 2 Community License Agreement.

Deployment Geography:

Global

Use Case:

Creators and professionals can use this model to generate high-quality images from text prompts, simplifying visual communication.

Release Date:

August 1, 2024

References

• Flux on Black Forest Labs
• Flux blog post

Model Architecture:

Architecture Type: Transformer and Convolutional Neural Network (CNN)
Network Architecture: Diffusion Transformer
LiheYoung/Depth-anything-large-hf leverages the DPT architecture with a DINOv2 backbone.

Input:

Input Type: Text Input Parameters: Text: 1D. Input Format: Text: String.
Other Properties Related to Input: Steps, Output Image Aspect Ratio, and Seed per the API Reference Page

Output:

Output Type: Image
Output Parameters: 2D
Output Format: Red, Green, Blue (RGB)
Other Properties Related to Output: Supported resolutions 1024x1024, 768x1344, 1344x768, 896x1152, 1152x896, 832x1216, 1216x832

Software Integration:

Runtime Engines:

• TensorRT

Supported Hardware Platforms:

• NVIDIA Blackwell
  
• NVIDIA Hopper
  
• NVIDIA Lovelace
  

Supported Operating Systems: Linux, Windows Subsystem for Linux

Model Version(s):

• FLUX.1-schnell

Training, Testing, and Evaluation Datasets:

Training Dataset:

• Data Collection Method by Dataset: Undisclosed
• Labeling Method by Dataset: Undisclosed

Properties (Quantity, Dataset Descriptions, Sensor(s)): Undisclosed

Testing Dataset:

• Data Collection Method by Dataset: Undisclosed
• Labeling Method by Dataset: Undisclosed

Properties (Quantity, Dataset Descriptions, Sensor(s)): Undisclosed

Evaluation Dataset:

• Data Collection Method by Dataset: Undisclosed
• Labeling Method by Dataset: Undisclosed

Properties (Quantity, Dataset Descriptions, Sensor(s)): Undisclosed

Inference:

Engine: TensorRT
Test Hardware: H100

Ethical Considerations:

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.

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