
MiroThinker: A deep research agent optimized for research and prediction. It achieves a 88.2 on the challenging BrowseComp benchmark. See Quick Start.
.pdf, .doc, .ppt, .xls, .jpg. Welcome to try it out! MiroThinker will continue to be maintained and iteratively upgraded, with the goal of becoming the best Research Agent you'll ever use! 📜 Click to expand older updates
Our new MiroThinker family represents a significant leap in building reliable agents for long-chain tasks. Engineered with enhanced post-training pipeline, our MiroThinker-1.7 family achieve SOTA performance in deep research tasks among open-source models.
Key Features
| Model Name | Parameters | Max Context | Max Tool Calls | HF Link |
|---|---|---|---|---|
| MiroThinker-1.7-mini | 30B | 256K | 300 | 🤗 link |
| MiroThinker-1.7 | 235B | 256K | 300 | 🤗 link |
MiroThinker-1.7 demonstrates strong general-research performance across a broad range of benchmarks, achieving 74.0%, 75.3%, 82.7% and 42.9% on BrowseComp, BrowseComp-ZH, GAIA-Val-165 and HLE-Text, respectively. MiroThinker-1.7 achieves SOTA performance on BrowseComp-ZH.

📦 Click to expand MiroThinker-v1.5 details
MiroThinker v1.5 is the world-leading open-source search agent that advances tool-augmented reasoning through interactive scaling — training the agent to handle deeper and more frequent agent-environment interactions as a third dimension of performance improvement, beyond model size and context length.

Key Features
| Agent Name | Base Agent | Max Context | Max Tool Calls | HF Link |
|---|---|---|---|---|
| MiroThinker-v1.5-30B | Qwen3-30B-A3B-Thinking-2507 | 256K | 400 | 🤗 link |
| MiroThinker-v1.5-235B | Qwen3-235B-A22B-Thinking-2507 | 256K | 400 | 🤗 link |
MiroThinker v1.5 demonstrates strong general-research performance across a broad range of benchmarks, achieving 39.2%, 69.8%, 71.5%, and 80.8% on HLE-Text, BrowseComp, BrowseComp-ZH, and GAIA-Val-165, respectively. These results surpass previous open-source agents and set the new world-leading BrowseComp performance.

📦 Click to expand MiroThinker-v1.0 details
Unlike previous agents that scale only model size or context length, MiroThinker v1.0 introduces interactive scaling at the agent level, systematically training the agent to handle deeper and more frequent agent–environment interactions as a third dimension of performance improvement. Interactive scaling leverages environment feedback and external information acquisition to correct errors and refine trajectories.

| Agent Name | Base Agent | Max Context | Max Tool Calls | HF Link |
|---|---|---|---|---|
| MiroThinker-v1.0-8B | Qwen3-8B | 256K | 600 | 🤗 link |
| MiroThinker-v1.0-30B | Qwen3-30B-A3B-Thinking-2507 | 256K | 600 | 🤗 link |
| MiroThinker-v1.0-72B | Qwen2.5-72B-Instruct | 256K | 600 | 🤗 link |
MiroThinker v1.0 demonstrates strong general-research performance across a broad range of benchmarks, achieving 37.7%, 47.1%, 55.6%, and 81.9% on HLE-Text, BrowseComp, BrowseComp-ZH, and GAIA-Text-103, respectively. These results surpass previous open-source agents and narrow the gap with commercial counterparts such as GPT-5-high.

📦 Click to expand MiroThinker-v0.2 details
In this new version, we introduced three key improvements:
Compared to v0.1, MiroThinker v0.2 delivers consistent gains across benchmarks. For example, scores improved from 57.3 → 64.1 on GAIA-Text-103 and from 17.0 → 29.4 on BrowseComp-ZH, reflecting substantial advancements in the model’s general research agent capabilities.
| Agent Name | Base Agent | Max Context | HF Link |
|---|---|---|---|
| MiroThinker-4B-SFT-v0.2 | Qwen3-4B | 64K | 🤗 link |
| MiroThinker-4B-DPO-v0.2 | Qwen3-4B | 64K | 🤗 link |
| MiroThinker-8B-SFT-v0.2 | Qwen3-8B | 64K | 🤗 link |
| MiroThinker-8B-DPO-v0.2 | Qwen3-8B | 64K | 🤗 link |
| MiroThinker-14B-SFT-v0.2 | Qwen3-14B | 64K | 🤗 link |
| MiroThinker-14B-DPO-v0.2 | Qwen3-14B | 64K | 🤗 link |
| MiroThinker-32B-SFT-v0.2 | Qwen3-32B | 64K | 🤗 link |
| MiroThinker-32B-DPO-v0.2 | Qwen3-32B | 64K | 🤗 link |
📦 Click to expand MiroThinker-v0.1 details
<img src="https://github.com/MiroMindAI/MiroThinker/raw/main/assets/gaia_text_103.png" width="98%" alt="MiroFlow Performance on GAI
$ claude mcp add MiroThinker \
-- python -m otcore.mcp_server <graph>