What is MiroThinker v1.5
MiroThinker v1.5 is MiroMind an open-source search agent model developed by the team. Through interactive scaling technology, the model deeply couples reasoning with the external environment, breaking the limitations of traditional large models that rely on massive parameters. The model has capabilities for proactive verification, multi-round validation, and anti-hallucination, enabling precise reasoning under conditions of incomplete information. MiroThinker v1.5 performs excellently in multiple benchmark tests, with low reasoning cost and strong performance, especially demonstrating capabilities beyond traditional large models at lightweight parameter scales, providing efficient and reliable intelligent solutions for research and practical applications.
Main features of MiroThinker v1.5
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Efficient search and reasoning: The model supports complex search tasks, can enhance reasoning capabilities through tools, quickly find and verify information, and provide accurate answers.
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Deep interaction capabilities: Through frequent interaction with the external environment, it obtains real-time data and supports multi-step reasoning and long-horizon reasoning.
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Multilingual support: It performs excellently in both Chinese (BrowseComp-ZH) and English (BrowseComp) benchmark tests, supporting multilingual tasks.
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Lightweight and high-performance: The model parameter scale ranges from 30B to 235B, with low cost, fast inference speed, and high cost-effectiveness.
Technical principles of MiroThinker v1.5
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Interactive Scaling：Emphasizes the interaction between the model and the external environment. Through the "reasoning - verification - correction" loop, external information is introduced as verification anchors to solve the logical collapse problem of traditional models.During the training phase, interaction capabilities are internalized. The model is encouraged to proactively verify and perform multi-round validation, avoiding probability-based hallucinated outputs.
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Time-sensitive training：The model is trained under strict timestamp constraints, can only reason based on past information, and verifies with evidence under the same constraints, eliminating Future Leakage. The modelthrough a dynamically evolving data synthesis system, simulates real-world temporal logic, improving the model's decision-making ability under uncertain conditions.
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Lightweight design：MiroThinker v1.5 deliberately controls the model parameter scale, avoids blindly pursuing ultra-large parameters, and uses more computing power for external information acquisition and interaction.Through the interactive reasoning mechanism, it uses small models to achieve the functions of large models, improving intelligence density.
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Anti-hallucination mechanism：Zero tolerance for reasoning paths lacking real basis. During training, outputs that rely only on statistical correlation or pattern memory are strictly penalized to ensure the reliability and authenticity of reasoning.
Project address of MiroThinker v1.5
- GitHub repository：https://github.com/MiroMindAI/MiroThinker
- HuggingFace model library：https://huggingface.co/collections/miromind-ai/mirothinker-v15
Application scenarios of MiroThinker v1.5
- Stock market prediction: By analyzing market dynamics, news events, and historical data, it accurately predicts stock trends and provides decision support for investors.
- New product R&D: Analyzes market trends, user needs, and competitive conditions, providing data support and innovative ideas for new product development.
- Healthcare: Analyzes medical data and public health trends, predicts disease outbreaks and transmission paths, and assists public health decision-making.
- Academic research assistance: Quickly locate relevant literature and research progress, providing researchers with directional suggestions and validation support.
- Market Trend Analysis: Analyze consumer behavior and market dynamics, predict market trends and demand changes, and help enterprises formulate marketing strategies.