# SAM 3: Segment Anything with Concepts

- id: src_01M569EE78CBJ4SQC0QQKR0697
- type: source · status: active · revision: 2
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=source_inspected, execution=not_run, review=unreviewed
- categories: T11 · tags: level:frontier, segmentation, text-prompted, concept-prompts, video-tracking, meta, code:python
- updated: 2026-10-18T01:24:11.055Z
- url: https://veyrul.com/sources/src_01M569EE78CBJ4SQC0QQKR0697

Source: https://github.com/facebookresearch/sam3

```json
{
  "archived": false,
  "checked_at": "2026-10-17T00:00:00.000Z",
  "parent_url": null,
  "usefulness": "Segments and tracks all instances matching a concept prompt (noun phrase and/or exemplars) in images and video, with inference and fine-tuning code. Text-driven roto selection for compositing and edit automation.",
  "source_type": "repository",
  "availability": "available",
  "dependencies": [
    "PyTorch (CUDA)"
  ],
  "source_owner": "Meta Superintelligence Labs",
  "next_check_at": "2026-10-18T00:00:00.000Z",
  "successor_url": null,
  "hardware_notes": "CUDA-compatible GPU with CUDA 12.6+ per README.",
  "known_limitations": [],
  "upstream_updated_at": "2026-10-14T23:45:15.000Z"
}
```

Evidence claims:
- [upstream_claim] README: repository provides inference and fine-tuning code, checkpoint download links and example notebooks; requires a CUDA-compatible GPU with CUDA 12.6 or higher. · locator: README, Installation · source: https://github.com/facebookresearch/sam3
- [upstream_claim] Paper abstract: SAM 3 detects, segments and tracks objects from concept prompts (noun phrases, image exemplars or both), built on a data engine with 4M unique concept labels; introduces SA-Co benchmark; reported roughly double the accuracy of existing systems on concept segmentation. · locator: arXiv abstract (v2, revised 2026-03-28) · source: https://arxiv.org/abs/2511.16719
- [sourced_fact] LICENSE is the 'SAM License' (last updated Nov 19, 2025): non-exclusive, worldwide, non-transferable, royalty-free limited license to use, reproduce, distribute and modify SAM Materials (code, weights, docs); redistribution must be under the same agreement; end uses tied to ITAR/trade controls, military or warfare, nuclear etc. are prohibited. · locator: LICENSE, sections 1(a)-(b) and use restrictions · source: https://github.com/facebookresearch/sam3
- [upstream_claim] Research review verdict at export: reviewed (as of 2026-10-17). Recorded by the research pipeline, not a hub review outcome; evidence.review stays unreviewed until an independent reviewer records one.

Rights:
- code: license=LicenseRef-Meta-SAM-License-2025-11-19 hosting=restricted redistribution=restricted modification=restricted training=unknown · Custom Meta 'SAM License' covers code and model weights together ('SAM Materials'); GitHub reports NOASSERTION; not OSI. Training-on-output terms not extracted. L07 2026-10-17: license_id set to LicenseRef-Meta-SAM-License-2025-11-19 (Custom Meta 'SAM License' (last updated Nov 19, 2025) covers code and weights.) · evidence: https://github.com/facebookresearch/sam3/blob/main/LICENSE
- model_weights: license=LicenseRef-Meta-SAM-License-2025-11-19 hosting=restricted redistribution=restricted modification=restricted training=unknown · Weights are within 'SAM Materials' under the same license; checkpoints are distributed via gated links per README (gating mechanism not verified). L07 2026-10-17: license_id set to LicenseRef-Meta-SAM-License-2025-11-19 (Custom Meta 'SAM License' (last updated Nov 19, 2025) covers code and weights.) · evidence: https://github.com/facebookresearch/sam3/blob/main/LICENSE

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