Encoder V1
Meta🇺🇸Frontier
MetaEncoder v1 produces embeddings for images, video, documents and text that suit search, clustering and comparison. Its decide function also answers closed-set questions about a state with probabilities.
Releases from frontier labs, major companies and research institutes — grouped by model, deduplicated across HuggingFace, OpenRouter and official blogs.
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Meta🇺🇸Frontier
MetaEncoder v1 produces embeddings for images, video, documents and text that suit search, clustering and comparison. Its decide function also answers closed-set questions about a state with probabilities.
Meta🇺🇸Frontier
Muse Ember is the smallest and most efficient model from Meta that’s designed for complex reasoning execution and the work agents repeat all day: tool calls, coding agent subtasks, routing,...
Meta🇺🇸Frontier
Meta coding model for agentic workflows with 816B total and 42B active MoE parameters, a 1M token context window, and text, image, video and audio input. NVFP4 checkpoints are offered for download on Hugging Face.
Meta🇺🇸Frontier
Meta announces Muse Wonder and Muse Wonder Full, which it calls its most capable models for personal and professional agentic tasks such as insurance claims, leases, and building apps. Muse Wonder is available via the Meta Model API, Muse Wonder Full only to Muse Code subscribers.
Meta🇺🇸Frontier
No description yet — the model card or announcement hasn't been summarised.
Meta🇺🇸Frontier
Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and coding workflows. It is designed to track information...
Meta🇺🇸Frontier
A dense 30B open-weight model from Meta for local agentic work, covering multi-step reasoning, tool use and image understanding. According to the sources it runs fully on a single GPU without cloud access.
Meta🇺🇸Frontier
Muse Spark 1.2 contributor tier is a reasoning model from Meta designed for developers who want to start building at an even lower cost. It’s meaningfully cheaper than Muse Spark...
Meta🇺🇸Frontier
Muse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with a 1M-token context...
Meta🇺🇸Frontier
No description yet — the model card or announcement hasn't been summarised.
Meta🇺🇸Frontier
Meta's multimodal MoE flagship: 17B active, 128 experts, 402B total, 1M-token context. Scout variant (16E, 109B) for lean deployments. Llama 5 is expected in H2 2026.