Muse Spark 1.1
Muse Spark 1.1 is a multimodal reasoning model from Meta Superintelligence Labs built for agentic tasks, coding, computer use, tool use, and multimodal understanding. The model improves on the original Muse Spark with stronger performance in planning, orchestration, long-context work, coding workflows, and external app interactions. Muse Spark 1.1 can manage a 1 million token context window, remember earlier actions, retrieve important information, compact context, and delegate tasks across parallel subagents. It is designed to operate across tools, MCP servers, custom skills, browsers, native apps, scripts, images, video, PDFs, and audio-based workflows. Developers can access Muse Spark 1.1 through the new Meta Model API public preview, while users can try it in Thinking mode in the Meta AI app and on meta.ai.
Learn more
Muse Video
Muse Video is Meta’s upcoming video generation model from Meta Superintelligence Labs, previewed alongside the launch of Muse Image. The model is built on the same pretraining foundation as Muse Image and is designed to generate high-fidelity videos with native audio support. Muse Video focuses on prompt adherence, visual realism, temporal consistency, and the ability to create short scenes with clear motion, continuity, and audio context. It can generate a wide range of video styles, including cinematic footage, UGC-style ads, animal scenes, product commercials, handheld point-of-view clips, and realistic moments with sound effects, voices, and music. Meta is continuing to improve areas such as audio-video synchronization and physically accurate fast motion before broader release. Coming soon to creators and Meta AI, Muse Video is positioned as a powerful tool for generating dynamic media across Meta’s creative ecosystem.
Learn more
Muse Code
Muse Code is Meta’s terminal coding agent, powered by Muse Spark 1.2, for handling complex software engineering tasks across large repositories. The agent can plan changes, write code, validate results, and coordinate multiple persistent subagents during development sessions. Muse Code uses async background agents that stay active throughout a session to reduce repeated information gathering and help complete multi-step tasks with less steering. Its runtime uses a local event log that records model calls, tool runs, approvals, and edits so sessions can be replayed and resumed after failures. Muse Code includes bundled skills such as /plan for approval-gated planning, /grill for stress-testing plans, and /goal for working toward completion. Built for AI developers and software teams, Muse Code helps automate coding workflows, long-running engineering tasks, debugging, and repository-level development.
Learn more
Unity Muse
Fueled by next-generation AI, Unity Muse enables creators of all skill levels to develop games and real-time 3D experiences lightning fast with simple text-based prompts.
Learn more
