DigestAI news desk

Cut through the AI noise.

Generative AI & Models

Pistis introduces 27B- and 9B-parameter multimodal models via new training framework

Researchers released the Pistis model family on arXiv, featuring two multimodal large language models built on Qwen3.6 and Qwen3.5. The 27B-parameter model uses Qwen3.6, while the 9B-parameter model is based on Qwen3.5. Both leverage a novel post-training framework called Interleaved Distillation and Reinforcement Learning (IDRL), which alternates between on-policy distillation and reinforcement…

1 source primary source

Key points

  • Pistis model family includes 27B-parameter (Qwen3.6-based) and 9B-parameter (Qwen3.5-based) multimodal LLMs
  • IDRL framework alternates distillation and reinforcement learning for stronger performance and stability
  • Pistis-Agentic variant excels in multimodal search and supports long-horizon agentic tasks

The framework produces two specialized variants per scale: Pistis-Thinking for deep multimodal reasoning and Pistis-Agentic for long-horizon planning, iterative reasoning, and tool use. Pistis-Agentic excels in multimodal search. The team also introduced Pistis-Auto-Harnessing (PAH), a system-level method that optimizes inference harnesses without altering model parameters or increasing interaction costs. Experiments show PAH improves performance without parameter updates.

Read the original at arXiv cs.AI · by Heyun Chen, Xiaohan Lan, Jiaxi Li, Zhilin Lu, Qi She, Weiwen Xu, Fei Yu, Yujie Zhong, Jinghuan Chen, Zijian Feng, Siyu Jiao, Yiheng Lin, Xinhao Wang, Sihan Yang, Jieyu You, Changbin Zhang, Hengyu Zhang, Xudong Zhang, Yunqing Zhao, Shuai Zheng primary sourceOpen source ↗
Topics · follow one to build your own front page
PistisQwen3.6Qwen3.5Pistis-ThinkingPistis-Agentic

The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

Comments

via GitHub Discussions

More in Generative AI & Models

All →

Related stories