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.