{"adoption": {"forks": 107, "observed_at": "2026-08-28T04:04:36.861396+00:00", "stars": 1398}, "canonical_url": "https://ross.abutalabs.com/products/giga-world-policy", "card": {"archived": false, "artifact_type": "library", "description": "GigaWorld-Policy: An Efficient Action-Centered World–Action Model", "domain": ["robotics", "machine-learning", "deep-learning", "artificial-intelligence"], "enriched": true, "function": ["machine-learning", "deep-learning", "llm-training", "simulation"], "health_score": 93, "homepage": null, "language": "Python", "license": null, "license_family": "other", "maturity": "active", "member_repos": ["open-gigaai/giga-world-policy"], "name": "open-gigaai/giga-world-policy", "platform": ["python"], "pushed_at": "2026-07-21T06:25:27+00:00", "repo": "open-gigaai/giga-world-policy", "stars": 1398, "tags": ["world-model", "robot-policy-learning", "action-model", "mixture-of-transformers", "real-time-inference", "robotics", "pytorch", "gpu", "linux"], "topics": [], "urls": [], "use_cases": ["train robot policies with world models", "real-time robot control with low latency inference", "learn robot manipulation policies from visual demonstrations", "run a world action model locally on a single GPU", "research action-conditioned world modeling for robotics"], "what_it_is": "GigaWorld-Policy is a World Action Model (WAM) for robot policy learning that jointly models actions and future visual observations during training while using action-only decoding at inference. Its 0.5 release uses a Mixture-of-Transformers architecture to achieve 85ms inference latency on a local RTX 4090 for real-time closed-loop robot control.", "when_to_avoid": ["you need a general-purpose vision-language model rather than a robot control policy", "you lack GPU hardware for training or inference", "you need a plug-and-play robot stack without ML research involvement"], "when_to_choose": ["you need efficient real-time robot policy inference on consumer GPUs", "you want to leverage future visual dynamics as dense supervision for policy learning", "you are researching world models or action models for robot control"]}, "data_as_of": "2026-08-30T08:39:29.467469+00:00", "members": [{"path": "/products/giga-world-policy", "repo": "open-gigaai/giga-world-policy", "role": "main", "score": 59}], "provenance": {"archived": {"kind": "observed", "observed_at": "2026-08-28T04:04:36.861396+00:00", "source": "github"}, "artifact_type": {"confidence": null, "enriched_at": "2026-08-30T04:39:13.849000+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "445fbcbb4877ed1d670c2a572657d853fc79599a32932e71444e0a0ba8957ee4", "fetched_at": "2026-08-28T04:04:36.861396+00:00", "kind": "readme", "missing": false, "url": "https://github.com/open-gigaai/giga-world-policy"}], "taxonomy_version": 1}, "description": {"kind": "observed", "observed_at": "2026-08-28T04:04:36.861396+00:00", "source": "github"}, "domain": {"confidence": null, "enriched_at": "2026-08-30T04:39:13.849000+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "445fbcbb4877ed1d670c2a572657d853fc79599a32932e71444e0a0ba8957ee4", "fetched_at": "2026-08-28T04:04:36.861396+00:00", "kind": "readme", "missing": false, "url": "https://github.com/open-gigaai/giga-world-policy"}], "taxonomy_version": 1}, "enriched": {"inputs": [], "kind": "computed", "method": "enrichment_status"}, "function": {"confidence": null, "enriched_at": "2026-08-30T04:39:13.849000+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "445fbcbb4877ed1d670c2a572657d853fc79599a32932e71444e0a0ba8957ee4", "fetched_at": "2026-08-28T04:04:36.861396+00:00", "kind": "readme", "missing": false, "url": "https://github.com/open-gigaai/giga-world-policy"}], "taxonomy_version": 1}, "health_score": {"inputs": ["days_since_push", "days_since_release", "archived"], "kind": "computed", "method": "health_v1"}, "homepage": {"kind": "observed", "observed_at": "2026-08-28T04:04:36.861396+00:00", "source": "github"}, "language": {"kind": "observed", "observed_at": "2026-08-28T04:04:36.861396+00:00", "source": "github"}, "license": {"kind": "observed", "observed_at": "2026-08-28T04:04:36.861396+00:00", "source": "github"}, "license_family": {"inputs": ["license"], "kind": "computed", "method": "license_family"}, "maturity": {"confidence": null, "enriched_at": "2026-08-30T04:39:13.849000+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "445fbcbb4877ed1d670c2a572657d853fc79599a32932e71444e0a0ba8957ee4", "fetched_at": "2026-08-28T04:04:36.861396+00:00", "kind": "readme", "missing": false, "url": "https://github.com/open-gigaai/giga-world-policy"}], "taxonomy_version": 1}, "member_repos": {"kind": "observed", "observed_at": "2026-08-28T04:04:36.861396+00:00", "source": "github"}, "name": {"kind": "observed", "observed_at": "2026-08-28T04:04:36.861396+00:00", "source": "github"}, "platform": {"confidence": null, "enriched_at": "2026-08-30T04:39:13.849000+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "445fbcbb4877ed1d670c2a572657d853fc79599a32932e71444e0a0ba8957ee4", "fetched_at": "2026-08-28T04:04:36.861396+00:00", "kind": "readme", "missing": false, "url": "https://github.com/open-gigaai/giga-world-policy"}], "taxonomy_version": 1}, "pushed_at": {"kind": "observed", "observed_at": "2026-08-28T04:04:36.861396+00:00", "source": "github"}, "repo": {"kind": "observed", "observed_at": "2026-08-28T04:04:36.861396+00:00", "source": "github"}, "stars": {"kind": "observed", "observed_at": "2026-08-28T04:04:36.861396+00:00", "source": "github"}, "tags": {"confidence": null, "enriched_at": "2026-08-30T04:39:13.849000+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "445fbcbb4877ed1d670c2a572657d853fc79599a32932e71444e0a0ba8957ee4", "fetched_at": "2026-08-28T04:04:36.861396+00:00", "kind": "readme", "missing": false, "url": "https://github.com/open-gigaai/giga-world-policy"}], "taxonomy_version": 1}, "topics": {"kind": "observed", "observed_at": "2026-08-28T04:04:36.861396+00:00", "source": "github"}, "urls": {"kind": "observed", "observed_at": "2026-08-28T04:04:36.861396+00:00", "source": "github"}, "use_cases": {"confidence": null, "enriched_at": "2026-08-30T04:39:13.849000+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "445fbcbb4877ed1d670c2a572657d853fc79599a32932e71444e0a0ba8957ee4", "fetched_at": "2026-08-28T04:04:36.861396+00:00", "kind": "readme", "missing": false, "url": "https://github.com/open-gigaai/giga-world-policy"}], "taxonomy_version": 1}, "what_it_is": {"confidence": null, "enriched_at": "2026-08-30T04:39:13.849000+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "445fbcbb4877ed1d670c2a572657d853fc79599a32932e71444e0a0ba8957ee4", "fetched_at": "2026-08-28T04:04:36.861396+00:00", "kind": "readme", "missing": false, "url": "https://github.com/open-gigaai/giga-world-policy"}], "taxonomy_version": 1}, "when_to_avoid": {"confidence": null, "enriched_at": "2026-08-30T04:39:13.849000+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "445fbcbb4877ed1d670c2a572657d853fc79599a32932e71444e0a0ba8957ee4", "fetched_at": "2026-08-28T04:04:36.861396+00:00", "kind": "readme", "missing": false, "url": "https://github.com/open-gigaai/giga-world-policy"}], "taxonomy_version": 1}, "when_to_choose": {"confidence": null, "enriched_at": "2026-08-30T04:39:13.849000+00:00", "kind": "inferred", "prompt_version": 1, "sources": [{"content_hash": "445fbcbb4877ed1d670c2a572657d853fc79599a32932e71444e0a0ba8957ee4", "fetched_at": "2026-08-28T04:04:36.861396+00:00", "kind": "readme", "missing": false, "url": "https://github.com/open-gigaai/giga-world-policy"}], "taxonomy_version": 1}}, "score": {"components": {"activity": 93, "longevity": 13, "rhythm": 41}, "computed_at": "2026-09-02T17:46:02.011165+00:00", "flags": ["no_license"], "formula": "round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)", "inputs": {"age_days": 183, "days_push": 43, "days_rel": 183, "gap_med": null, "n_releases_24m": 1}, "score": 59, "version": 2}, "staleness": {"enrichment_outdated": false, "low_confidence": false, "scrape_days": 9, "stale_scrape": false}}