Meta AI models

Muse Spark 1.2 is Meta's reasoning model for complex agentic tasks, accepting text, images, video, audio, and PDF documents and returning text, with a 1,048,576-token context window. Called via the Responses API, it supports cross-turn reasoning replay, tool-calling loops, built-in web search grounding, and file inputs, with configurable reasoning effort and structured JSON output. Meta reports strong results on multi-file refactors, extended debugging sessions, and whole-repository generation.

Muse Spark 1.1 is Meta's first paid agentic reasoning model, accepting text, image, video, and PDF input and returning text, with a 1,048,576-token context window and 131,072 max output tokens. It thinks before it answers with reasoning tokens billed as output, actively manages and compacts its own context on long-running workflows, and exposes native tool calling, structured output, parallel tool calling, and built-in web search grounding with inline citations via the Responses API.