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Brief Introduction#

I. The First Shot of the 2026 New Year: Why MiroThinker 1.5 is Breaking Global Records?#

In early 2026, the global large language model market is turbulent. Just as debates about GPT-5-High or Gemini-3-Pro’s parameter counts were heating up, MiroMind, led by Tianqiao Chen and top scholar Jifeng Dai, officially released its flagship search agent model—MiroThinker 1.5.

Dubbed the “most powerful small cannon in the agent domain,” this model stunned the developer community upon release. In multiple rigorous benchmark tests, MiroThinker 1.5 demonstrated exceptional “intelligence efficiency ratio”:

  • HLE-Text (Human-Level Exam): Achieved 39.2%, far surpassing models of similar scale.
  • BrowseComp (Web Retrieval Benchmark): Scored a super-high 69.8%, directly breaking the record held by ChatGPT-Agent and entering the global top tier.
  • GAIA-Val-165: Achieved a validation score of 80.8%.

MiroThinker 1.5, Entering the Top Performance Tier with 30B Parameters

The most incredible part is that MiroThinker 1.5’s parameter count is only 1/30th of mainstream models. It doesn’t rely on “rote memorization” but achieves performance exceeding Kimi-K2-Thinking at an extremely low cost through active interaction and real-time reasoning.

II. The Giants Behind the Tech: Tianqiao Chen and Jifeng Dai’s AGI Utopia#

If you followed the internet 20 years ago, you know Tianqiao Chen; if you follow neuroscience, you know TCCI. Tianqiao Chen has invested over one billion US dollars in neuroscience, and his deep involvement over six to seven years has given him unique, profound insights into AGI (Artificial General Intelligence).

Why now? Why MiroMind?

From Professor Jifeng Dai’s account, we see a startup story with strong “DeepSeek characteristics.” Tianqiao Chen provides funding and the AGI vision, while Jifeng Dai contributes top-tier technology and team leadership. This tripartite structure of “capital + vision + technical expertise” drastically reduces communication costs.

MiroMind’s mission is very clear: Embrace open source, uphold technological idealism. This is a team with flat hierarchies, transparent information flow, composed of driven, excellent young talent. They are not taking the old path of “piling on compute and parameters” but are pioneering a new track of “discovery-based intelligence.”

III. Deep Dive: Interactive Scaling & “Scientist Mode” Reasoning#

The core reason MiroThinker 1.5 achieves “punching above its weight” lies in its unique Interactive Scaling mechanism.

1. From “Test-Taker” to “Scientist”#

Traditional large models are like “test-takers,” relying on memorization of massive corpora for probability prediction. Once the knowledge base is outdated or logic breaks, hallucinations occur. MiroThinker 1.5, however, adopts a “scientist mode”:

  • Propose Hypotheses: For complex problems, first break them down into verifiable sub-problems.
  • External Evidence Gathering: Actively initiate retrieval and real-time interaction with the internet.
  • Feedback Correction: Revise initial judgments based on evidence.

2. Time-Sensitive Training Sandbox#

To solve the “cheating” behavior caused by models “predicting the future” during training, MiroMind developed a Time-Sensitive Training Sandbox. During training, the model can only access information before the current timestamp, forcing it to learn to handle the incomplete, noisy environment of the real world. This is also why it can provide highly “deterministic” analyses when predicting the GTA 6 release date, World Cup win probabilities, or A-share market trends.

IV. Complete Local Deployment Tutorial for MiroThinker 1.5#

To facilitate developers, MiroMind released the model as open source. Below is an ultra-simplified local deployment tutorial compiled by 【MiroMind Beginner’s Net】.

1. Environment Preparation#

Ensure your local device meets the minimum configuration:

  • 30B Version: Recommended VRAM ≥ 48GB (e.g., A6000 or dual 3090/4090).
  • 235B Version: Recommended 8-card H100/H800 cluster.
  • System: Ubuntu 22.04+, CUDA 12.1+.

2. Code & Weight Download#

Bash

bash

# Clone the official repository
git clone https://github.com/MiroMindAI/MiroThinker
cd MiroThinker

# Download weights (take 30B as an example)
# Please visit Hugging Face: miromind-ai/MiroThinker-v1.5-30B

3. Launch Using the MiroFlow Framework#

MiroMind provides the accompanying open-source framework MiroFlow, specifically designed for managing the multi-step interaction flow of Agents.

Python

python

from miromind import MiroThinker

# Initialize the model
model = MiroThinker.load("path/to/weights-30B")

# Enable professional search mode
response = model.think("Which team has the highest probability of winning the 2026 World Cup final?", search_mode=True)

print(response.reasoning_process) # View the chain of thought
print(response.final_answer)     # View the final conclusion

4. Common Troubleshooting#

  • VRAM Overflow: Try enabling 4-bit quantization.
  • Search Timeout: Check if the Serper or Google Search API Key is configured correctly.

V. Why MiroMind is the Most Noteworthy AGI Organization in 2026?#

At a time when the Log curve of Scaling Law is flattening, MiroMind has found a new growth curve.

  1. High Intelligence Efficiency Ratio: Single API call cost is only $0.07, which is 1/20th of Kimi-K2-Thinking.
  2. Ultra-Fast Interaction: Compared to the slow feedback of traditional Search GPTs, MiroThinker 1.5 completes the entire “search-reflect-correct-conclude” process within two minutes.
  3. Predictive Power: It has consecutively topped the Polymarket prediction charts, its practical capabilities already validated by the world’s top markets.

Tianqiao Chen once changed the way China entertained itself via the internet. Now, he is trying to change the way humanity accesses truth through MiroMind.

🚀 Experience & Community#

Webmaster’s Note: This site, 【MiroMind Beginner’s Net】, will continue to provide the latest evaluations and localized private deployment solutions for the MiroThinker model. If you are a developer, investment researcher, or AI enthusiast, be sure to bookmark this site!

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