CM3leon
CM3leon (pronounced "chameleon") is a multimodal generative model from Meta AI, introduced in July 2023, that handles both text-to-image and image-to-text generation in a single architecture.
Multimodal AI
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Chameleon (Meta AI)
Chameleon is a family of early-fusion, token-based mixed-modal foundation models from Meta AI's Fundamental AI Research (FAIR) group that represents both images and text as discrete tokens in a single unified…
ImageBind
ImageBind is a multimodal model from Meta AI (its Fundamental AI Research lab) that learns a single joint embedding space across six different modalities: images and video, text, audio, depth, thermal…
Llama 3.2
Llama 3.2 is a family of four open-weight large language models released by Meta on September 25, 2024, comprising lightweight 1 billion and 3 billion parameter text-only models for on-device AI and the 11…
Llama 3.2 Vision
Llama 3.2 Vision is the set of multimodal (image-plus-text) models in Meta's Llama 3.2 family, released on September 25, 2024 at the Meta Connect 2024 developer conference.
Llama 4 Scout and Maverick
Llama 4 Scout and Llama 4 Maverick are open-weight, natively multimodal AI large language models developed by Meta and released on April 5, 2025.
MetaCLIP
MetaCLIP (Metadata-Curated Language-Image Pre-training) is a data curation recipe and a family of vision-language models from Meta AI, introduced in the 2023 paper "Demystifying CLIP Data" by Hu Xu, Saining…
Muse Glimmer
Muse Glimmer is an open-weight text-and-image model developed by Meta AI for local agent and coding workloads. Meta released the model on August 10, 2026 under the identifier meta-models/Muse-Glimmer-30B.
Muse Image
Muse Image is a proprietary image-generation and editing system developed by Meta Superintelligence Labs, a division of Meta.
Muse Spark
Muse Spark is a proprietary multimodal reasoning model developed by Meta Superintelligence Labs (MSL), the artificial intelligence division Meta reorganized in 2025.
Perception Encoder
Perception Encoder (PE) is a family of vision and vision-language encoders from Meta AI's Fundamental AI Research (FAIR) group, released in April 2025
data2vec
data2vec is a self-supervised learning framework from Meta AI (then Facebook AI Research) that applies the same training method to three different input types: speech, computer vision, and text.