Segment Anything Model (SAM) 3.1

Detect, segment and track objects in images and video on Meta Model API, with nothing to host or tune.

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SAM 3.1 architecture

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Leading perception with purpose-built inference

SAM 3.1 is our leading perception model for object detection, segmentation and tracking, served on inference built specifically for its DETR architecture. Get production throughput on day one, with nothing to stand up or tune.

Integrated with other Meta models

SAM 3.1 shares its envelope, keys, docs and billing with every other Meta model, so segmentation and video tracking drop smoothly into the pipeline you already have. Reason and generate with Muse Spark, turn speech into text with Muse Voice Transcribe, and detect, segment and track objects with SAM 3.1, all through Meta Model API.

Detection, segmentation and tracking in one model

Most multimodal models give you labels and bounding boxes and leave the rest to you. SAM 3.1 detects the objects, returns pixel-precise segmentation masks and tracks them through video with identity preserved, all from a single call. Zero-shot, with no training data, fine-tuning or extra models required.