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SAM 3.1: Faster and More Accessible Real-Time Video Detection and Tracking With Multiplexing and Global Reasoning

Meta AI Blog

Meta released SAM 3.1, an updated version of its Segment Anything Model that processes video object tracking more efficiently through a technique called object multiplexing. The model doubles processing speed from 16 to 32 frames per second on a single H100 GPU by tracking up to 16 objects in a single forward pass instead of processing each object separately. This enables real-time object tracking in complex videos while reducing GPU resource requirements, making the technology feasible on smaller hardware.

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Update March 27, 2026:

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TLDRocket 21 July 2026

The open-weight AI model market hit an inflection point today as Alibaba and Kimi released trillion-parameter competitors that challenge the closed-model orthodoxy—just as Washington moved to restrict them. Alibaba's Qwen 3.8 Max (2.4 trillion parameters) and Kimi K3 (2.8T) are going open-weight, with K3 ranking first on Frontend Web App Arena and fourth on agentic benchmarks, signaling that scale and transparency can coexist. The timing matters: while U.S. policymakers weigh layered restrictions on Chinese open models, technical experts are pushing back hard, arguing that closed gardens actually hurt security and competition more than they help. The real fragmentation risk isn't technical—it's regulatory.

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SAM 3.1: Faster and More Accessible Real-Time Video Detection and Tracking With Multiplexing and Global Reasoning

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