LongCat-Flash-Thinking: Revolutionizing Open-Source AI Reasoning with 560B MoE Architecture

In the rapidly evolving world of artificial intelligence, large language models (LLMs) are pushing the boundaries of what’s possible in reasoning and problem-solving. Today, we’re diving deep into LongCat-Flash-Thinking, a groundbreaking 560-billion-parameter Mixture-of-Experts (MoE) model developed by the Meituan LongCat Team. This open-source powerhouse activates an average of 27 billion parameters, making it both efficient and powerful for tasks like math, coding, and agentic reasoning. If you’re an AI enthusiast, researcher, or developer searching for the latest in open-source AI reasoning models, this blog post is your ultimate guide. We’ll explore its architecture, training pipeline, key features, benchmarks, and how …