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SAM 2

Segment Anything Modelv2.1Current
byMetaMeta(ai lab)
Released July 29, 2024
Context1 tokens
Price (In / Out)Free / Free
CategoryImage Model
Max Output1 tokens

About SAM 2

SAM 2, or Segment Anything Model 2, is Meta FAIR’s promptable visual segmentation model for images and videos. The official repository provides inference code, SAM 2.1 checkpoints, example notebooks, training resources, and benchmark tables for SA-V, MOSE, and LVOS video object segmentation tasks.

Capabilities

visionimage segmentationvideo segmentationpromptable segmentationopen weights

Input Modalities

imagevideovisual prompts

Output Modalities

segmentation masksmasklets

Technical Details

API Identifier
facebook/sam2-hiera-large
Category
Image Model
Context Window
1 tokens
Max Output Tokens
1 tokens

Tags

sam-2segment-anythingimage-segmentationvideo-segmentationmetafairopen-weightscomputer-vision

Benchmarks

Performance scores for SAM 2 across standard benchmarks.

SA-V test J&Fofficial SAM 2 README, sam2.1_hiera_large · Sep 2024
79.5%
MOSE val J&Fofficial SAM 2 README, sam2.1_hiera_large · Sep 2024
74.6%
LVOS v2 J&Fofficial SAM 2 README, sam2.1_hiera_large · Sep 2024
81%
Speed FPS A100official SAM 2 README, sam2.1_hiera_large · Sep 2024
39.5%

Pricing

Token pricing for SAM 2 API usage.

Input Tokens

Free

per million tokens

Output Tokens

Free

per million tokens

Pricing Calculator

Input cost$0.00
Output cost$0.00
Estimated monthly cost$0.00

Open checkpoints and code are provided under Apache 2.0 in the official repository; compute costs depend on the user’s hardware or cloud environment.