sam3
by facebook
Concept-level segmentation with open-vocabulary detection and video tracking
facebook/sam3mixpeek://image_extractor@v1/facebook_sam3_v1Overview
SAM 3 is Meta's unified foundation model for concept-level segmentation. It detects, segments, and tracks objects using open-vocabulary text prompts or visual exemplars, handling 270K+ unique concepts. It bridges the gap between detection and segmentation in a single model.
On Mixpeek, SAM 3 enables concept-driven content analysis: specify any concept in text and SAM 3 will find, segment, and track every instance across images and video.
Architecture
Decoupled detector-tracker architecture sharing a vision encoder. 848M total parameters. Uses a presence token for discriminating closely related prompts. Trained on 4M+ automatically annotated concepts.
Mixpeek SDK Integration
// No extractor parameter takes a Hugging Face model id (checked against
// GET /v1/discovery/extractors, which returns 13), so sam3 runs
// on your side and the output is upserted through POST
// /v1/namespaces/{namespace_id}/documents/upsert. On Enterprise the other
// path is to upload the weights instead: POST /v1/namespaces/{id}/models
// accepts the huggingface format and a custom plugin loads them.
const res = await fetch(
"https://api.mixpeek.com/v1/namespaces/ns_your_namespace/documents/upsert",
{
method: "POST",
headers: {
Authorization: "Bearer API_KEY",
"Content-Type": "application/json",
},
body: JSON.stringify({
collection_id: "col_your_collection",
documents: [
{
document_id: "asset-00412",
// Boxes, masks, depth maps and anomaly scores are structured
// results, not vectors. They go in payload and are reachable
// through pre_filters on a retriever, not through similarity.
payload: {
detections: modelOutput,
source_key: "archive/2026/asset-00412",
},
},
],
}),
},
);
// No managed alternative for an open label set. Two extractors do emit a
// bbox, for the one thing each detects: document_graph_extractor@v1 per
// layout block, face_identity_extractor@v1 per face. Nothing ships that
// returns masks, depth maps or anomaly scores.Capabilities
- Open-vocabulary detection + segmentation (270K+ concepts)
- Video tracking with mask propagation
- Text and visual exemplar prompts
- Concept-level exhaustive segmentation
- Outperforms OWLv2, DINO-X, Gemini 2.5 on benchmarks
Use Cases on Mixpeek
Benchmarks
| Dataset | Metric | Score | Source |
|---|---|---|---|
| SA-V (video seg.) | J&F | 83.2 | SAM 3 model card |
Performance
Common Pipeline Companions
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Specification
Research Paper
SAM 3: Segment Anything with Concepts
arxiv.orgBuild a pipeline with sam3
Add this model to a processing pipeline alongside other extractors. Combine with retrieval stages for end-to-end search.
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