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MiroThinker v1.5 - An open-source search agent model released by MiroMind.

MiroThinker v1.5 is an open-source search agent model from the MiroMind team. Through interactive extension techniques, the model deeply couples inference with the external environment, breaking away from the limitations of traditional large models that rely on massive parameters.

What is MiroThinker v1.5?

MiroThinker v1.5 is an open-source search agent model from the MiroMind team. Through interactive extension technology, the model deeply couples inference with the external environment, breaking the limitations of traditional large models that rely on massive parameters. The model possesses proactive verification, multi-round validation, and anti-illusion capabilities, enabling accurate inference even with incomplete information. MiroThinker v1.5 performs excellently in multiple benchmark tests, exhibiting low inference costs and strong performance, especially demonstrating capabilities surpassing traditional large models with a lightweight parameter scale, providing an efficient and reliable intelligent solution for research and practical applications.

Main features of MiroThinker v1.5

  • Efficient Search and ReasoningThe model supports complex search tasks, enhances reasoning capabilities through tools, quickly finds and verifies information, and provides accurate answers.
  • Deep interactive capabilitiesIt acquires real-time data through frequent interaction with the external environment, supporting multi-step reasoning and long-term reasoning.
  • Multilingual supportIt performs well in both Chinese (BrowseComp-ZH) and English (BrowseComp) benchmark tests and supports multilingual tasks.
  • Lightweight high performanceThe model has a parameter size between 30B and 235B, low cost, fast inference speed, and high cost-effectiveness.

Technical Principles of MiroThinker v1.5

  • Interactive Scaling:It emphasizes the interaction between the model and the external environment, and introduces external information as a verification anchor point through the "reasoning-verification-correction" cycle to solve the problem of logical collapse in traditional models.During the training phase, interactive capabilities are internalized, and the model is encouraged to actively seek verification and undergo multiple rounds of validation to avoid illusionary outputs based on probability.
  • Time-sensitive training:The model is trained under strict timestamp constraints, can only extrapolate from past information, and is verified using equally constrained evidence, thus preventing future leakage.By using a dynamic evolutionary data synthesis system, the temporal logic of the real world is simulated, thereby improving the model's decision-making ability under uncertain conditions.
  • Lightweight design:MiroThinker v1.5 deliberately controls the scale of model parameters to avoid blindly pursuing ultra-large parameters, and uses more computing power for external information acquisition and interaction.By using an interactive reasoning mechanism, the functions of a large model can be achieved with a small model, thereby increasing the intelligence density.
  • Anti-hallucination mechanism:There is zero tolerance for reasoning paths lacking real evidence. During training, strict penalties are imposed on outputs that rely solely on statistical correlation or pattern memory to ensure the reliability and authenticity of reasoning.

MiroThinker v1.5 project address

  • GitHub repository: https://github.com/MiroMindAI/MiroThinker
  • HuggingFace model libraryhttps://huggingface.co/collections/miromind-ai/mirothinker-v15

Application Scenarios of MiroThinker v1.5

  • Stock market forecastBy analyzing market dynamics, news events, and historical data, it accurately predicts stock trends and provides decision support for investors.
  • New product developmentAnalyze market trends, user needs, and competitive landscape to provide data support and innovative ideas for new product development.
  • HealthcareAnalyze medical data and public health trends to predict disease outbreaks and transmission routes, and support public health decision-making.
  • Academic research assistanceIt can quickly locate relevant literature and research progress, providing researchers with directional suggestions and verification support.
  • Market Trend AnalysisAnalyze consumer behavior and market dynamics, predict market trends and changes in demand, and help businesses develop marketing strategies.
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