Meta Sam 3: Segment Anything with Text, Clicks and Concepts
Meta SAM 3 is the latest iteration of Meta AI Research's segmentation model, designed to identify and track objects in images and videos. It offers various prompt methods, including text, exemplar boxes, and visual clicks, allowing for flexible and precise segmentation. The model is built to enhance creative workflows and is intended for real-world applications such as social media editing and research.
- ▪Meta SAM 3 can segment and track objects in images and videos using simple prompts.
- ▪It supports multiple prompt types, including text, exemplar boxes, and positive/negative clicks.
- ▪The model is designed for real-world applications, including features for Instagram and research collaborations.
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Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Sam3ai |
| Canonical URL | https://sam3ai.com/ |
| Publication time | Sun, 24 May 2026 00:58:40 +0000 |
| Retrieval time | 2026-05-24T01:37:28.736Z |
| Last seen | 2026-05-24T01:37:28.736Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | FAWJoWXh7qzj |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Next-Gen Segment Anything Meta SAM 3 - Segment Anything with Text, Clicks & Concepts Meta SAM 3 lets you point, type, or show an example and it instantly finds, segments, and tracks every object you care about in any image or video. Get Started Now Learn More Download Overview What Is Meta SAM 3 AI? Meta SAM 3 AI (Segment Anything Model 3) is Meta AI Research’s newest “segment anything” model that can detect, precisely segment (mask), and track objects in images and videos using simple prompts. What makes SAM 3 special is how you can tell it what to segment: Key Values and Vision Text prompts: type a short phrase like “person” or “car” and it masks matching objects. Exemplar prompts: draw a box around one example object, and it masks all similar objects in the scene.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Sam3ai.
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