Releases

Meta Platforms closed with an estimated public equity market capitalization of $1.8474 trillion based on its Nasdaq-listed META shares.

Meta reported $60.801 billion in quarterly revenue, $15.848 billion in net income and headcount of 75,472 as of June 30, 2026.

Meta launched an API for developers to access and build with Muse Spark 1.1.

Meta released Muse Spark 1.1 and made it available through Meta Model API.

Meta announced Muse Video, a generative video model with native audio support, as coming soon.

Meta released Muse Image for instruction-following image generation, precise editing and multi-reference composition.

Meta released training code for Brain2Qwerty v1 and v2; v2 performs real-time non-invasive sentence decoding from brain recordings.

Meta introduced an AI business agent that can learn from a company's public content and support customer conversations across Meta surfaces.

Meta Superintelligence Labs introduced Muse Spark, a multimodal model designed for efficient broad intelligence.

Meta released an efficiency update adding object multiplexing and up to 32-frame-per-second multi-object video tracking on one H100.

Meta released a tri-modal foundation model that predicts high-resolution human brain activity from video, audio and language.

Meta published an infrastructure update describing four MTIA chips developed across two years for large-scale AI inference.

Meta and World Resources Institute released a DINOv3-based global forest-canopy model with improved accuracy and detail.

Meta released a unified multimodal model for separating sounds from complex mixtures using natural prompts.

Meta announced content partnerships to bring more real-time news and information into Meta AI responses.

Meta released a model for estimating human body pose and shape from a single image.

Meta released a model for reconstructing 3D objects and scenes from a single image.

Meta released SAM 3 for text-, exemplar- and visual-prompted detection, segmentation and tracking in images and video.

Meta released speech-recognition models covering more than 1,600 languages plus an open corpus for 350 underserved languages.

Meta launched Vibes, a feed in the Meta AI app and meta.ai for creating, remixing and sharing AI-generated short videos.

The US General Services Administration added Meta's Llama models to OneGov to support federal-agency AI adoption.

Meta announced an EMG wristband that translates subtle muscle signals into controls for Meta Ray-Ban Display glasses.

Meta announced AI glasses with an in-lens color display for visual Meta AI answers, messages, navigation and captions.

Meta launched second-generation Ray-Ban Meta glasses with longer battery life, 3K video and expanded Meta AI features.

Meta released DINOv3, a scaled self-supervised vision foundation model for high-quality visual features.

Mark Zuckerberg outlined Meta's strategy to build personal superintelligence and distribute it through consumer products.

Meta announced Hyperion, a Louisiana AI data-center campus planned to scale to five gigawatts of compute capacity.

Meta consolidated its frontier AI efforts into Meta Superintelligence Labs, led by Chief AI Officer Alexandr Wang with Nat Friedman overseeing AI products and applied research.

Meta and EssilorLuxottica introduced performance-focused Oakley Meta HSTN AI glasses.

Meta made a $14.3 billion non-voting minority investment in Scale AI and expanded the companies' commercial relationship; Scale was valued above $29 billion.

Meta released V-JEPA 2 for video understanding, physical-world prediction and zero-shot robot planning.

Meta launched a standalone personalized AI assistant app built with Llama 4 and connected to meta.ai and AI glasses.

Meta released vision encoders for images and video designed to support recognition, localization and multimodal systems.

Meta released a multimodal safety classifier for Llama 4 inputs and outputs.

Meta previewed Behemoth as a teacher model for the Llama 4 family; it was not made generally available.

Meta released Llama 4 Maverick, a natively multimodal mixture-of-experts model for general AI workloads.

Meta released Llama 4 Scout, a natively multimodal mixture-of-experts model with a 10-million-token context window.

Meta began rolling out its AI assistant across 41 European countries and 21 overseas territories.

Meta released PARTNR, a benchmark, dataset and planning model for human-robot collaboration on household tasks.

Meta researchers introduced a non-invasive deep-learning system for decoding typed sentences from EEG and MEG brain recordings.

Meta's first TRIBE brain-response model formed the foundation for its award-winning Algonauts 2025 entry; Meta's later TRIBE v2 announcement identifies the original model as 2025 work.

Meta released a behavioral foundation model for controlling virtual humanoid agents.

Meta released a multilingual 70B instruction model with performance comparable to larger Llama 3.1 models.

Meta released research on a multimodal language model that freely mixes text and speech.

Meta introduced foundation models for video generation, personalized video, editing and synchronized audio.

Meta published improved SAM 2.1 checkpoints and developer tooling.

Meta released a 90B multimodal model for image understanding.

Meta released an 11B multimodal model for image understanding.

Meta released a compact 1B text model for on-device use.

Meta released a compact 3B text model for on-device use.