# orca-wm/Orca

Orca: The World is in Your Mind

Repository: https://github.com/orca-wm/Orca
Canonical: https://ross.abutalabs.com/products/orca-wm-orca
Language: Python
License Family: other
Last push: 2026-08-21T10:20:44+00:00

## Health v2 (maintenance only)
Score: 57/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 98, release rhythm 35, longevity 4
- inputs: {"age_days": 60, "days_push": 12, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, young, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1038, forks 58 (observed 2026-08-28T04:03:19.558089+00:00)

## What it is
Orca is a general world foundation model from BAAI centered on Next-State-Prediction, learning a unified world latent space from visual and language signals. The repository provides inference code and the Orca-4B checkpoint for world latent learning and downstream text/image readouts.

## Use cases
- generate predictions of future world states from video and language inputs
- run inference with a pretrained 4B world model checkpoint
- extract world latent representations for downstream tasks
- research unified next-state prediction instead of next-token or next-frame objectives
- train lightweight readout decoders on a frozen world model encoder
- explore scaling behavior of world foundation models

## When to choose
- you need a pretrained multimodal world model for research on state prediction
- you want to probe or read out a unified world latent with text and image decoders
- you are studying world-model scaling or unconscious/conscious learning from video

## When to avoid
- you need a production-ready application or fine-tuning pipeline (fine-tuning code is not yet released)
- you need a small lightweight model (the 0.8B checkpoint is not yet available)
- you require a permissively licensed project (no license is specified)

## Facets
- artifact type: library
- maturity: experimental
- function: machine-learning, deep-learning, llm-inference, video-processing, nlp
- domain: artificial-intelligence, machine-learning, deep-learning, computer-vision
- platform: python
- tags: world-model, next-state-prediction, foundation-model, multimodal, world-latent, research-code, video-understanding, natural-language-processing, gpu, linux

## Member repositories
- orca-wm/Orca (main) score 57

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:19.558089+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:04:18.373467+00:00, confidence not recorded.
  - readme: https://github.com/orca-wm/Orca (fetched 2026-08-28T04:03:19.558089+00:00, sha bb76d5f954b7)
- Data as of 2026-08-30T08:39:29.467469+00:00.