Agentic task orchestration
The model can gather context, make a plan, and delegate work across parallel subagents for tasks that span multiple apps and services.
Muse Spark 1.1 is a multimodal reasoning model from Meta Superintelligence Labs for agentic tasks, coding, computer use, and multimodal understanding. It is available in public preview through the Meta Model API and in Thinking mode in the Meta AI app and on meta.ai.
Muse Spark 1.1 is a multimodal reasoning model from Meta Superintelligence Labs designed for agentic tasks. Meta positions it as an upgrade over Muse Spark, with stronger tool and computer use, coding, and multimodal understanding.
The model is available through the new Meta Model API in public preview, and it is also available in Thinking mode in the Meta AI app and on meta.ai. The launch emphasizes long-context work, orchestration across tools and subagents, and workflows that require both perception and action.
The model can gather context, make a plan, and delegate work across parallel subagents for tasks that span multiple apps and services.
Meta says Muse Spark 1.1 zero-shot generalizes to new native tools, MCP servers, and custom skills.
The model is trained to actively manage a very large context window, retain earlier actions, and compact work while preserving important steps.
It can switch between scripting, clicking, and batching actions depending on whether automation or direct interaction is faster.
Meta says it performs better on real-world coding tasks such as bug fixing, feature implementation, and code migrations.
The model can work with visual and audio inputs and produce outputs useful for tasks like image and video captioning or visual-to-code workflows.
Useful when a task requires planning, context collection, and coordinated execution across multiple tools or services.
Fits workflows that involve unfamiliar interfaces, changing requirements, or long sessions where the model needs to preserve context.
Applicable to debugging, implementing features, tracing issues across a codebase, and validating changes in agentic coding setups.
Useful when a workflow starts from images, video, or audio and ends in an action such as captioning, code generation, or browser-based execution.
Meta highlights a workflow where the model uses smartphone video, extracts useful photos, reasons about the product, and helps create a Facebook Marketplace listing.
Muse Spark 1.1 is Meta's multimodal reasoning model for agentic tasks, released as an upgrade over Muse Spark.
Developers can access it through the Meta Model API in public preview, and end users can use it in Thinking mode in the Meta AI app and on meta.ai.
Meta highlights planning and orchestration across tools, computer use, coding, and multimodal understanding.
Yes. Meta says the model can actively manage a 1 million token context window and preserve important steps over long workflows.
The provided source material does not include pricing details, and the pricing page was not available in the collected evidence.
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