MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention

Researcher focused on computer vision, multimodal learning, and generative AI. His public homepage says he is currently with Stepfun, after serving as a principal scientist at SenseTime Research and a researcher at Microsoft Research Asia, and that he earned a PhD in computer science from Tsinghua University.

Chunlin Li is a research scientist at MiniMax.

AI researcher whose public work includes large language models, vision-language models, and multimodal systems. His public profile notes prior work as a senior algorithm expert at Alibaba and co-authorship of Qwen technical reports.

Research scientist at MiniMax focused on reasoning, efficient large language models, reinforcement learning, and multimodal understanding and generation.

Alibaba senior technology leader and researcher associated with Qwen. Public profiles list him with Alibaba Group, and official Alibaba Cloud coverage identifies him as a chief technology officer leading large-model work.

Jie Zhou is a Moonshot AI contributor and co-author of Kimi k1.5: Scaling Reinforcement Learning with LLMs.

Researcher working on speech and multimodal language models, including MiniMax-Speech and related speech understanding work.

Lead of foundation models at MiniMax working on large language models, multimodal pretraining, and efficient training systems. He completed a PhD in computer science at Tsinghua University.

Research scientist at MiniMax AI Research interested in large language models, machine learning, and computer vision. He earned a PhD from Shanghai Jiao Tong University and previously worked at Alibaba DAMO Academy on vision-language reasoning and video understanding.

Research scientist at MiniMax AI Research focused on large language models, machine learning, and recommendation systems. He received a PhD from Shanghai Jiao Tong University and previously worked at Alibaba DAMO Academy on machine learning and distributed databases.

Research scientist at MiniMax AI Research focused on reinforcement learning, reasoning, multimodal learning, large language models, and large-scale distributed systems. He received a PhD in machine learning from Carnegie Mellon University.

Researcher focused on reinforcement learning, large language model reasoning, and multimodal foundation models; coauthor of Janus-Pro and MiniMax-M1.

Research scientist at MiniMax AI Research whose interests include large language models, machine learning, and code intelligence. He earned a PhD from Nanyang Technological University and previously worked on code intelligence, search, and recommender systems at Alibaba DAMO Academy.

Researcher working on efficient large language models and reasoning systems, including MiniMax-M1.

Researcher focused on reinforcement learning and multimodal foundation models; arXiv author results include the MiniMax-M1 paper.

Research scientist at MiniMax AI Research focused on large language models, reinforcement learning, and AI for science. He received a PhD from Peking University and has published at NeurIPS, ICML, ICLR, AAAI, and IJCAI.

Research scientist at MiniMax AI Research focused on AI for science, large language models, and deep generative models. He received a PhD from Stanford University and a bachelor's degree in computer science from Rice University.

Research scientist at MiniMax AI Research focused on multimodal large language models, AI agents, and reasoning. He previously worked on multimodal understanding and generation and holds a master's degree from Tsinghua University.

Researcher at Moonshot AI and co-author of the Kimi K2.5 report on visual agentic intelligence.

Researcher at Moonshot AI and co-author of the Kimi K2.5 report on visual agentic intelligence.

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