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IQuest Research releases IQuest-Q1 technical report

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ZhiZhi Innovation Research Institute publicly released the complete technical report for IQuest-Q1, disclosing the 30 Benchmark results of this open-source base model with 320B total parameters and 15B activated parameters. The report states that the model scores 52.7 and 51.8 on AutomationBench and τ³-Banking respectively, ranking first among the comparison models listed in the report; training used approximately 29T Tokens and over 1 million containerized executable tasks, and suppresses Reward Hacking through a three-layer mechanism of environment cleanup, execution checks, and trajectory auditing.

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Oct 23
  1. XiaohongshuXiaohongshu · Tech Just Now· Discussion
    IQuest-Q1 public technical report(opens the original post in a new tab)
  2. WeChat · AI Era (Xinzhiyuan)
    ZhiZhi Innovation Research Institute publicly releases the complete IQuest-Q1 technical report: million-level task training and anti-cheating mechanisms for a 320B open-source base model

    IQuest Research publicly released the complete technical report for IQuest-Q1, disclosing the 30 Benchmark results of this open-source base model with 320B total parameters and 15B activated parameters. The model scored 52.7 and 51.8 on AutomationBench and τ³-Banking respectively, ranking first among the comparison models listed in the report; training used approximately 29T Tokens and more than 1 million containerized executable tasks, and three layers of mechanisms—environment cleanup, execution checks, and trajectory auditing—were used to suppress Reward Hacking.

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