Beeble AI has announced version 3.0 of its model SwitchLight, described as “the best Video-to-PBR model in the world”. The tool converts video footage into physically based rendering (PBR) passes suitable for VFX and relighting workflows.
Key improvements
According to Beeble’s official release, the model is now a true video model: it processes multiple frames simultaneously rather than treating each frame individually and applying a post-deflicker step. This approach is said to produce smoother, more stable temporal results in moving footage.
Beeble also claims that SwitchLight 3.0 has been trained on a dataset ten times larger than that of the previous version. The company states this broader dataset captures a wider range of lighting conditions, materials, and environments, yielding more realistic results.
The desktop application, Beeble Studio, now supports 4 K resolution input, 16-bit EXR output, and local GPU processing for video up to one hour in length. The cloud-based version has been upgraded to SwitchLight 3.0 as well, with no price increase for existing users.
The release further highlights improved preservation of fine surface detail, such as facial wrinkles, hair strands, and fabric texture. The update also claims to correct several artefacts present in earlier versions, including the green-tinted normals sometimes seen on top of subjects’ heads.
Workflow and platform details
Beeble confirms that all footage processed through its cloud application now uses the new model automatically, without additional user input. For the local version, Beeble Studio, the software downloads and activates the updated model upon launch. No changes to pricing or subscription structure are mentioned.
What is not yet clear or independently verified
Beeble’s claims of “the best Video-to-PBR model” and “unmatched quality” remain vendor statements; no third-party benchmarks or peer-reviewed tests have been published. Hardware specifications for the local GPU workflow, including minimum VRAM and platform compatibility beyond Windows, are not detailed in the announcement. However, as with any new AI-driven tool, studios should conduct thorough in-pipeline testing before adoption. Verification under real-world production conditions remains essential to ensure consistency and compatibility with existing workflows.
