VAST has open-sourced EdenLive, a generative AI model capable of real-time video re-rendering of coarse game engine output. The release includes 5B and 14B parameter models, which can achieve over 24 FPS at 720p on an Nvidia RTX 5090.
This release marks a shift toward hybrid rendering pipelines where traditional engines handle logic while generative models manage high-fidelity aesthetics. By achieving playable frame rates on consumer-grade Nvidia hardware, VAST lowers the barrier for developers to implement stylized, AI-driven environments without the overhead of manual asset creation. For the streaming ecosystem, this technology suggests a future where interactive content can be personalized or re-skinned dynamically at the edge. Watch for improvements in visual consistency over long-duration runs and the handling of high-frequency character interactions to determine if this can move beyond simple puzzles into mainstream gaming.
The industry is seeing rapid adoption of generative AI for short-form video as platforms look to automate asset creation and personalization.
VAST has open-sourced its EdenLive model, a system that transforms game engine output into detailed, stylized video in real-time. By decoupling game logic from visual rendering, the 5B parameter model achieves 24.7 FPS at 720p on an Nvidia RTX 5090, enabling developers to create AI-driven environments without manual asset creation.
EdenLive is an open-source generative video model that allows developers to transform coarse game engine output into high-fidelity, stylized video in real-time.
The 5B parameter version of EdenLive achieves 24.7 FPS at 720p on a single Nvidia RTX 5090 GPU, and 29.8 FPS on an H100.
The 5B and 14B model weights are released under the Apache 2.0 license, though the vision encoders and workbenches carry more restrictive licenses.
The system architecture separates upstream game logic from the generative renderer, which allows developers to maintain testable world states while applying AI-driven aesthetics.
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