同一天开源新模型，一推理一编程，MiniMax和月之暗面开卷了

Core Insights - The article discusses the launch of new AI models by domestic large model manufacturers, specifically highlighting MiniMax-M1 and Kimi-Dev-72B as significant advancements in the field of open-source AI models [1][9]. Group 1: MiniMax-M1 - MiniMax-M1 is introduced as a long-context reasoning LLM capable of handling an input of 1 million tokens and an output of 80,000 tokens, making it one of the most powerful models in terms of context length [2][19]. - The model demonstrates exceptional capabilities in interactive applications, such as creating web applications and visualizing algorithms, with a focus on user-friendly UI components [5][8]. - MiniMax-M1 has been trained using a novel reinforcement learning algorithm called CISPO, which optimizes model performance by focusing on important sampling weights rather than token updates, achieving faster convergence compared to previous methods [20][23]. - The model's performance in various benchmarks shows it surpasses other open-weight models, particularly in software engineering and long-context tasks, with a notable score of 56.0% on the SWE-bench Verified benchmark [29][25]. Group 2: Kimi-Dev-72B - Kimi-Dev-72B is presented as a powerful open-source programming model that achieved a new state-of-the-art (SOTA) score of 60.4% on the SWE-bench Verified benchmark, showcasing its capabilities in code generation [10][37]. - The model employs a collaborative mechanism between BugFixer and TestWriter roles, enhancing its ability to fix bugs and write tests effectively [40][45]. - Kimi-Dev-72B underwent extensive mid-training using high-quality real-world data, which significantly improved its performance in practical error correction and unit testing [41][42]. - The model's design includes a unique outcome-based reward mechanism during reinforcement learning, ensuring that only effective code fixes are rewarded, thus aligning with real-world development standards [43][44].