Source-led brief
Today, we’re excited to introduce Muse Spark 1.1, the latest model from Meta Superintelligence Labs and a significant upgrade from Muse Spark. Muse Spark 1.1 is a multimodal reasoning model built for agentic tasks, with major gains in tool and computer use, coding, and multimodal understanding.
Muse Spark 1.1 delivers exceptional performance in personal agentic tasks that require planning and orchestration across a range of external apps and services. It zero-shot generalizes to new native tools, MCP servers, and custom skills.
It tackles complex projects significantly faster than Muse Spark, as it is trained to orchestrate multi-agent systems to optimize end-to-end latency. As the main agent, it can gather context, make a plan, and delegate execution across parallel subagents. As a subagent, it adheres to its job, understands available tools, and knows when to escalate back to the main agent.
Muse Spark 1.1 can actively manage its context window of 1 million tokens. It remembers actions, retrieves information from much earlier work, and compacts in a way that keeps the critical steps needed for later work.
Thai editorial note
บทความนี้อยู่ในหมวดการใช้งาน AI ส่วนบุคคล และคัดสรรจากแหล่งข้อมูลต้นฉบับเพื่อใช้เป็นจุดเริ่มต้นในการศึกษา ทีมบรรณาธิการควรตรวจสอบรายละเอียด ราคา ความพร้อมใช้งาน และเงื่อนไขในประเทศไทยก่อนนำไปใช้งานจริง
Verification
- Original source: ai.meta.com
- Discovery: Agent-Reach / Exa
- Clean extraction: jina-reader
- This page is a source summary, not an independent product review.
Source: ai.meta.com ↗