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What is FLUX 3 Action?

FLUX 3 Action is a dynamic 7B model designed to improve action prediction in robotics and other high-latency environments. It is founded on the multimodal FLUX 3 backbone and has been rigorously pretrained on extensive datasets that include images, videos, and audio, with a significant emphasis on video materials. Following this, it enters a joint video-action training and fine-tuning phase that is specifically tailored for various robotic applications and action frameworks. By processing instructions, visual data from cameras, and robot joint angles, FLUX 3 Action can forecast motor commands while also anticipating visual results, allowing robots to execute actions, reassess their environment, and refine their plans accordingly. Unlike traditional methods that separate visual prediction from control, this model merges future video predictions with action commands, effectively using insights gained from its comprehensive video pretraining to enhance robot control strategies. Impressively, its single-step 7B model boasts a success rate of 38.3% on the RoboLab-120 benchmark, underscoring its practicality in real-world scenarios. Additionally, this novel fusion of action and perception represents a groundbreaking leap forward in the domain of robotic control, paving the way for more sophisticated and capable robotic systems. As technology advances, the implications of such an integrated approach could lead to even more intelligent and responsive robots in various applications.

What is FLUX 3?

FLUX 3 is a state-of-the-art multimodal foundation model that seamlessly combines learning from images, videos, and audio within a unified framework, adeptly capturing the relationships between objects, the dynamics of motion, and the sounds produced by various events. Through the innovative Self-Flow methodology, it synchronizes the generation and interpretation of diverse modalities in a single architecture, ensuring a reciprocal influence among them—where sounds reflect impacts, movements follow physical principles, and future actions are shaped by previous experiences. This model excels in merging different modalities, enabling the concurrent generation of images, videos, and realistic audio in response to text prompts or visual and auditory references. Its capabilities in video production are remarkable, offering features such as text-to-video transformations, image-based video animations, video editing, generative extensions for both video and audio, precise control over transitions with keyframes, support for multilingual dialogue, dynamic text animations, and the ability to produce content in various styles and aspect ratios, including complex multi-shot sequences with agentic chaining. Furthermore, FLUX 3 marks a substantial advancement in multimodal AI, granting unprecedented opportunities for creativity and flexibility in crafting immersive, interactive content that engages users on multiple sensory levels. This innovative model not only enhances content creation but also opens new avenues for applications across industries, making it a pivotal tool in the evolution of artificial intelligence.

Media

Media

Integrations Supported

Integrations Supported

Collart AI
FLUX 3 Image
FLUX Upscale

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Black Forest Labs

Date Founded

2024

Company Location

Germany

Company Website

bfl.ai/models/flux-3-action

Company Facts

Organization Name

Black Forest Labs

Date Founded

2024

Company Location

Germany

Company Website

bfl.ai/

Categories and Features

AI Models

Not specified

AI World Models

Not specified

Open-Weight AI Models

Not specified

Categories and Features

AI Image Models

Not specified

AI Video Models

Not specified

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