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MiroThinker
MiroThinker is a deep research agent optimized for complex research and prediction tasks. Our latest models, MiroThinker-1.7, achieves 74.0 and 75.3 on the BrowseComp and BrowseComp Zh, respectively.
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01
At a glance.
A compact read before the deeper capability notes and official setup links.
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Core features.
Feature cards focus on what the tool helps users do, not generated setup commands.
MiroThinker: A deep research agent optimized for research and prediction.
Our proprietary agent MiroThinker-H1 achieves leading performance on BrowseComp and BrowseComp-ZH among open-source and commercial models.
\[2026-01-23\] 🎉 We have brought two important updates to MiroThinker online: (a) Core Research Report Generation: Deep Research online reports now support generation, preview, and sharing.
MiroThinker will continue to be maintained and iteratively upgraded, with the goal of becoming the best Research Agent you'll ever use!
\[2026-01-05\] 🎉🎉 We release MiroThinker-v1.5, a series of open-source deep research agents optimized for financial prediction.
MiroThinker-v1.5-235B scores 39.2% on HLE-Text, 69.8% on BrowseComp, 71.5% on BrowseComp-ZH, and 80.8% on GAIA-Val-165, setting a new state-of-the-art among search agents.
Introducing interactive scaling as a third dimension of performance improvement, MiroThinker v1.0 supports 256K context window and up to 600 tool calls per task.
\[2025-09-11\] MiroThinker-72B-Preview ranked 4th in this week's FutureX benchmark.
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Agent / Skill / MCP / Workflow fit.
This panel keeps technical format separate from the user-facing AI category.
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Official setup path.
Generated install snippets are intentionally not mirrored here because they drift. The page links to source-owned setup docs instead.
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Evidence and adoption notes.
These notes help a user decide whether to investigate the official project further.
Source repository last pushed at 2026-04-25T05:23:54Z.
Generated from source metadata; confirm operational details in the official project before adopting it.
Review the upstream license, maintenance activity, and issue history before using it in production.
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