sam3.1

by facebook

7x faster multi-object tracking via Object Multiplex shared-memory architecture

270Kdl/month

848Mparams

HuggingFace Use in Pipeline

Identifiers

Model ID

facebook/sam3.1

Feature URI

mixpeek://image_extractor@v1/facebook_sam31_v1

Overview

SAM 3.1 is Meta's update to the Segment Anything Model 3 that introduces Object Multiplex, a shared-memory approach for joint multi-object tracking. Instead of processing each object independently, SAM 3.1 bundles all tracked objects into a single forward pass with global reasoning, delivering 7x faster inference at 128 objects on a single H100 GPU while improving accuracy on 6 of 7 video segmentation benchmarks.

On Mixpeek, SAM 3.1 replaces SAM 3 as the default segmentation model for video analytics pipelines involving multiple simultaneous objects. The Object Multiplex architecture halves VRAM usage (8GB to 4GB FP16) while doubling throughput from 16 to 32 FPS, making multi-object tracking practical for production-scale video processing.

Architecture

Same detector-tracker architecture as SAM 3 (848M parameters) with Object Multiplex extension. Shared-memory joint processing of up to 16 objects per forward pass. DETR-based detector conditioned on text prompts, geometric prompts, and image exemplars. Global reasoning across all tracked objects simultaneously.

Mixpeek SDK Integration

import { Mixpeek } from "mixpeek";

const mx = new Mixpeek({ apiKey: "API_KEY" });

await mx.collections.ingest({
  collection_id: "my-collection",
  source: { url: "https://example.com/video.mp4" },
  feature_extractors: [{
    name: "segmentation",
    version: "v1",
    params: {
      model_id: "facebook/sam3.1",
      enable_multiplex: true
    }
  }]
});

Capabilities

7x faster than SAM 3 at 128 tracked objects (H100)
Object Multiplex: joint multi-object tracking in single forward pass
Improved on 6/7 VOS benchmarks including +2.0 on MOSEv2
Half the VRAM of SAM 3 (4GB vs 8GB FP16)
32 FPS multi-object tracking on H100

Use Cases on Mixpeek

Multi-object video tracking at scale — people, products, vehicles across surveillance feeds

Brand and logo tracking across advertising content with dozens of simultaneous objects

Production video editing with real-time multi-object segmentation and masking

Benchmarks

Dataset	Metric	Score	Source
MOSEv2 (video seg.)	J&F	+2.0 over SAM 3	Meta, Mar 2026 — SAM 3.1 Release
SA-V (video seg.)	J&F	Improved on 6/7 benchmarks	Meta, Mar 2026 — SAM 3.1 Release