Viggle releases JST-2, a physics-native world model that builds 3D scenes in about a second and rig-free animated characters, free in its PINOC app and via API

Why it matters

【Key points】

Viggle, best known for its meme-video app, released JST-2 on Oct 19 (15:20 UTC), which it calls a "physics-native" world foundation model. Instead of learning in pixel or video space, it represents the world as persistent "atoms" in 3D space, each with an explicit xyz position plus learned vectors for attributes and dynamics, and uses one architecture to generate scenes, characters and motion.

Scenes: JST-2 turns text or images into explorable 3D scenes, decoded as Gaussian splats that render locally in the browser. Viggle says a scene takes about one second on an NVIDIA B200 at under $0.01 of inference, versus roughly 5–6 minutes for World Labs' Marble. It keeps up to 64 views as spatial context for expanding a scene step by step, and can rebuild environments from sparse real photos.

Characters and motion: one image, even cropped or partly hidden, becomes a full-body 3D character that can be animated without separate rigging, and full-body motion can be generated from text or video and applied to standard rigs. In Viggle's blind tests against Meshy 7.1, Tripo H3.1 and HY-Motion-1.0, among others, JST-2 comes out ahead.

It is free to try in the PINOC browser app and available through an API and MCP.

【Verifiable】

Launch page: https://viggle.ai/jst2

Announcement: https://x.com/ViggleAI/status/2112202242048528540

Character benchmark: https://viggle.ai/research/jst2-character

【Our read】

1. Most world models learn from video and reconstruct 3D afterwards. JST-2 models 3D directly; if the speed and cost hold up, interactive scene building gets much cheaper.

2. All comparisons and blind tests are Viggle's own, and the Marble timing counts model inference only. Independent tests are needed.

3. It targets games, animation and robot simulation at once, but robotics use is still a stated direction with no published results.