Topics / #world-model

World-model projects on GitHub

World models that learn predictive representations of environments for planning and generation.

As of , the most-starred World-model projects on GitHub are utopia (8.4K stars), vllm-omni (7.2K stars) and FluxVLA (749 stars). GitHub.Locker tracks 7 World-model repositories with 17.4K stars combined. The fastest-growing on October 18 was utopia, with +28 stars in a day.

7Projects
17.4KStars in total
+45Stars in a day
Browse in the catalog →github.com/topics/world-model ↗

Hot right now

Most stars gained in a day · Oct 18

+28

utopia

deeplethe/utopia · ★ 8.4K

Utopia is an open-source enterprise world model from DeepLethe: a self-hosted knowledge system that turns documents into a bitemporal knowledge graph you can search, chat with and reason over, running entirely on hardware you control.

+17

vllm-omni

vllm-project/vllm-omni · ★ 7.2K

vLLM-Omni is an inference and serving framework that extends vLLM beyond text-only LLMs to omni-modality models, handling text, image, audio, video, and action outputs.

The all-time top

7 projects · by stars

  1. #1 · deeplethe/utopia

    utopia

    Utopia is an open-source enterprise world model from DeepLethe: a self-hosted knowledge system that turns documents into a bitemporal knowledge graph you can search, chat with and reason over, running entirely on hardware you control.

    8.4K
  2. #2 · vllm-project/vllm-omni

    vllm-omni

    vLLM-Omni is an inference and serving framework that extends vLLM beyond text-only LLMs to omni-modality models, handling text, image, audio, video, and action outputs.

    7.2K
  3. #3 · FluxVLA/FluxVLA

    FluxVLA

    FluxVLA is a full-stack engineering platform for embodied AI covering the whole loop from data to real-robot deployment for vision-language-action (VLA) models, built to lower the engineering barrier for VLA research and development.

    749
  1. 4

    cadence

    450muellerberndt/cadence · Python

    Cadence is an open research library toward general intelligence: a NumPy collection of 'brains' that compute by settling into an equilibrium and learn by detuning it, aiming to acquire skills from live experience the way animals and humans do.

  2. 5

    HarnessEval-W

    308MirroS-Lab/HarnessEval-W · Python

    HarnessEval-W is an agentified evaluation pipeline for benchmarking world/video-generation models: instead of a brute-force scalar score, it decomposes each evaluation case into sub-questions answered by specialized sub-agents, then aggregates the evidence into a transparent, auditable verdict.

  3. 6

    dreamforge

    130rzc156/dreamforge · Python

    Dreamforge is a research pipeline that mines a robot policy's own failure states, uses a latent world model (CEM) to imagine corrective actions, and verifies each correction by replaying it in the real simulator before claiming it helps.

  4. 7

    object-permanence

    97hokindeng/object-permanence · Python

    This is the official codebase for the paper 'Training Object Permanence in World Models' (arXiv:2609.28654). It bundles a Blender-based data factory that renders videos of objects persisting through occlusion, plus a training stack that teaches this behavior to a world model on AWS Trainium2.

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