MiroThinker

MiroThinker is a professional-grade, open-source search agent designed to transform how you conduct deep research and information seeking. While traditional AI models often rely on internal patterns to "guess" answers, MiroThinker acts as a digital researcher. It proactively uses external tools, browses the live web, and iteratively corrects its own logic to solve high-difficulty tasks that require more than just a simple chat response.

Built for analysts, researchers, and developers, MiroThinker bridges the gap between basic AI assistants and specialized deep-research tools. It addresses the core challenge of AI hallucinations by enforcing a "no evidence, no statement" policy, ensuring that every insight is grounded in verifiable data retrieved through multi-step analysis.

Key Features

🔍 Interactive Scaling & Self-Correction MiroThinker uses a unique feedback loop that allows it to refine its search strategy in real-time. If the model encounters conflicting evidence or realizes a search path is a dead end, it acknowledges the error and adjusts its approach, mimicking the critical thinking process of a human expert.

🛠️ Extensive Tool Augmentation Equipped to handle up to 400 tool calls per task, this agent can navigate complex workflows that involve searching the web, executing code, and analyzing data. This high capacity for tool interaction means you can delegate multi-layered research projects that would typically overwhelm standard AI models.

🧠 Long-Horizon Reasoning with 256K Context With a massive 256K context window, MiroThinker maintains a "memory" of vast amounts of information across long-form research sessions. This allows you to feed it extensive documents or have it synthesize dozens of web sources without losing track of the original research objective.

📉 Resource-Efficient Performance The 30B parameter version of MiroThinker delivers high-tier performance—surpassing several larger closed-source models—while remaining accessible enough to run on modest hardware. This brings "expert-level" reasoning to individual users and small teams without the need for massive enterprise infrastructure.

Use Cases

Deep Market Intelligence If you need to analyze the 2026 outlook for solid-state batteries, MiroThinker won't just summarize old data. It will search for the latest white papers, compare corporate financial reports, and cross-reference industry news to produce a comprehensive report complete with cited sources.

Technical Troubleshooting & Coding When faced with a complex software bug, the agent can search documentation, test potential code snippets, and iteratively debug the solution. It doesn't just provide a code block; it verifies the logic against real-world technical requirements.

Academic Literature Review Researchers can use MiroThinker to track down specific citations and summarize the evolution of a particular scientific theory. The model's ability to "step outside" its training data ensures that the information provided includes the most recent publications available on the web.

Why Choose MiroThinker ?

MiroThinker v1.5 stands out by prioritizing verifiable depth over conversational speed. According to benchmark data, it achieved a 69.8% accuracy rate on the BrowseComp test—outperforming ChatGPT-Agent—and a 71.5% accuracy on the BrowseComp-ZH Chinese language benchmark.

The primary advantage is its "Efficiency-to-Intelligence" ratio. By using a 30B parameter architecture to achieve results typically reserved for models ten times its size, MiroThinker offers a cost-effective path to high-end research. Furthermore, as a fully open-source framework, it provides complete transparency in how the agent reasons and interacts with tools, which is essential for users who require data sovereignty and auditability.

Conclusion

MiroThinker marks a transition from AI as a "chatbot" to AI as a "thinking partner." By focusing on evidence-based retrieval and the willingness to self-correct, it provides a level of reliability that is often missing in generative AI. This tool is designed for those who value the accuracy of the journey as much as the final answer, turning complex information seeking into a structured, automated, and highly precise process.