​The world's first open-weight, large-scale hybrid-attention reasoning model

​Join us for the inaugural technical seminar on MiniMax-M1 — the world’s leading open-source LLM for long-context reasoning, featuring a groundbreaking 1 million-token input and 80K-token output window. This session offers an exclusive opportunity to connect with top minds in AI and gain deep insights into the architecture, performance, and use cases of M1.

​What to Expect

​This online seminar will be the first official deep dive into the core innovations behind M1. Members of the development team will present technical overviews covering model design, inference performance, and practical applications. The event will also include panel discussions and a live Q&A session to foster open exchange within the global AI community.

​📢 Speakers & Panelists

• ​Junjie Yan – CEO/CTO, MiniMax

• ​Jun Qing - Technical Staff, MiniMax

• ​Jiayuan Song – Technical Staff, MiniMax

• ​Shunyu Yao – Research Scientist, Anthropic

• ​Junxian He – Assistant Professor, HKUST

• ​Wenhu Chen – Assistant Professor, University of Waterloo

• ​Songlin Yang – PhD Student, MIT CSAIL

• ​Arthur Zucker – Head of Transformers, Hugging Face

• ​Kaichao You – Core Developer, vLLM

• ​Akim Tsvigun - Senior ML Solutions Architect, Nebius

• ​Arjun Krishna - AI Researcher, Writer

• ​Liangsheng Yin - Core Developer, SGLang

• ​Nick Comly - Inference Product Lead, NVIDIA

​🧠 Agenda

​Technical Keynote

• ​Model Architecture & Algorithm Design – 20 min

​Panel Discussions

• ​Model & Algorithm – 20 min

• ​Inference – 20 min

​Q&A Session

• ​Open Discussion and Audience Questions – 15–20 min

​📅 Date & Time

​Thursday, July 10, 2025

• ​4:00 PM (PST)

• ​7:00 PM (EST)

• ​7:00 AM (CST/Beijing Time, July 11)

​Format: Zoom (Online Only) / Limited seats

​Get to know MiniMax-M1 at Hugging Face, GitHub, and Tech Report