Matrix-Game 2.0 Launches as a Powerful Open-Source Alternative to Genie 3

SINGAPORE, Aug. 12, 2025 /PRNewswire/ -- The SkyWork AI Technology Release Week officially kicked off on August 11. From August 11 to August 15, a new model will be unveiled each day, covering cutting-edge models for core multimodal AI scenarios.

A week ago, DeepMind released a major update to its interactive world model--Genie 3--enabling real-time, long-sequence generation. This advancement has drawn significant attention to world models. However, Genie 3 was not open-sourced, leaving the community to speculate about its implementation.

On August 12, Skywork unveiled an upgraded version of the self-developed Matrix series' interactive world model--Matrix-Game 2.0. It also delivers interactive, real-time, long-sequence generation in general scenarios. To drive progress in interactive world modeling, Matrix-Game 2.0 has been fully open-sourced, marking the industry's first open-source solution for real-time, long-sequence, interactive generation in general scenarios.

Matrix-Game 2.0 open source addresses:

--  Technical report: https://github.com/SkyworkAI/Matrix-Game/blob/main/Matrix-Game-2/assets/pdf/report.pdf
--  Project homepage: https://matrix-game-v2.github.io/
--  HuggingFace: https://huggingface.co/Skywork/Matrix-Game-2.0
--  GitHub: https://github.com/SkyworkAI/Matrix-Game

Matrix-Game 2.0 achieves a breakthrough in real-time generation and long-sequence handling. Compared to its predecessor, the 2.0 version prioritizes low-latency, high-frame-rate performance for extended interactions, enabling stable 25 FPS continuous video generation across complex scenes. Its generation length scales to minute-long sequences, drastically improving temporal coherence and real-world usability.

While delivering a significant boost in inference speed, Matrix-Game 2.0 maintains precise comprehension of physical laws and scene semantics. It enables users to freely explore, manipulate, and construct virtual environments in real time through simple instructions--yielding well-structured, detail-rich, and logically coherent virtual spaces.

With these capabilities, Matrix-Game 2.0 not only breaks down the barriers between content generation and interaction but also unlocks new possibilities for cutting-edge applications such as virtual humans, game engines, and embodied AI. It provides a robust technical foundation for building a universal virtual world.

Currently, Matrix-Game 2.0 boasts three core advantages:

High-frame-rate, real-time long-sequence generation: The model supports fluid movement (forward/backward, left/right) and camera/view rotation. Users can intuitively control characters in the scene via simple commands. The system generates seamless footage in real time at 25 FPS, enabling minute-long interactive sequences in a single session. Character movements are lifelike, smooth, and precisely responsive.

Cross-scenario generalization capability: The model demonstrates exceptional cross-domain adaptability. It is not only suitable for specific task scenarios but also supports simulations of diverse styles and environments--including urban, wilderness, and other spatial types, as well as realistic, oil-painting, and various visual styles.

Enhanced physical consistency: The model demonstrates a deeper understanding of physical rules. Characters generated by the model exhibit physically plausible movements when navigating complex terrains such as steps and obstacles, which improves immersion and controllability.

The open-source release of Matrix-Game for interactive video generation underscores Skywork's strategic foresight in AI development. This initiative will accelerate development across Skywork's multi-model AI ecosystem. Moving forward, Skywork remains committed to pioneering and open-sourcing advanced AI solutions. By collaborating with global developers and users, we aim to build next-generation platforms that accelerate the global advancement of AGI.

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SOURCE Skywork AI pte ltd