Micius-Flash: Lightweight Agentic Intelligence for Engineering

Hongcheng Gao, Weiheng Li, Yipeng Wei, Yu Lei, Shuo Sun, Yi Li, Yajiao Wang, Jie Luo, Jianwei Wen, Xinyi Zhou, Hongda Li, Yibing Zhang, Henghui Sun, Yufan Zhou, Tianfang Hao, Naihao Xue, Hailong Qu, Jingjing Zhou, Peng Xu, Yongzheng Wei, Yichen Zhu, Ziying Wang, Yibo Wang, Jianshu Zeng, Yuhang Lei, Zeqiang Wang

Micius-Flash: Lightweight Agentic Intelligence for Engineering: 8 upvotes on Hugging Face Daily Papers, #18 of 39 papers on 2026-11-11. Day-by-day upvote history.

Upvotes over time

It had 6 upvotes by its first day, 8 upvotes by the next day, 8 upvotes by day 3, 8 upvotes by day 7, and has 8 now. It ranked #63 of 133 papers in its week and #190 of 340 in its month.

We introduce Micius-Flash, a 27-billion-parameter model for engineering with native multimodal input, deep reasoning and a 256K-token context window. We design the Micius data pipeline as a knowledge-tree-driven data flywheel comprising three stages: knowledge tree construction and expansion, data synthesis, and quality validation with hard-example augmentation. From this data, we train expert models for semiconductor knowledge and reasoning, hardware coding, and semiconductor multimodal understanding, along with agentic experts. Subsequently, we employ Multi-Teacher On-Policy Distillation (MOPD) to supervise training on sequences generated by Micius itself, thereby integrating the capabilities of these expert models into a unified model. On more than 20 datasets with about 15K records, Micius-Flash averages 64.2% on hardware code benchmarks, 15.0 points above a same-size baseline. It scores 62.4% on a semiconductor-specific agent benchmark, exceeding the same-size baseline by 17.2 points. We further develop Micius Harness for industrial applications, connecting the model to specialized tools, including EDA tools and KiCad, as well as execution environments. Case studies in PCB design, chip design workflow automation, and software development demonstrate the model's ability to use tool execution feedback for multi-step planning, code debugging, and iterative verification. We release Micius as an open-source model to advance the development of agents for science and engineering.

Paper page on Hugging Face · arXiv

Data: hysts-bot-data/daily-papers-stats and the Daily Papers API. Open data: tardellirs/paper-pulse-data. Sister project: Model Pulse, the download history of every model on the Hub.