刚刚，DeepSeek发了“终极版”

Core Insights - DeepSeek has released an updated model, DeepSeek-V3.1-Terminus, which improves upon the previous version by enhancing language consistency and fixing bugs related to unexpected character outputs [1][7][20] - The model has been open-sourced, allowing broader access and potential community contributions [1][7] Performance Improvements - Benchmark tests show that DeepSeek-V3.1-Terminus has achieved performance improvements ranging from 0.2% to 36.5% compared to DeepSeek-V3.1, with notable enhancements in the Human's Last Exam (HLE) test, which assesses high-level knowledge and reasoning capabilities [3][5] - In non-Agent evaluations, the model's performance in MMLU-Pro improved from 84.8 to 85.0, and in HLE, it increased from 15.9 to 21.7 [5] Bug Fixes - The previous version had a significant bug where the model would output random characters, which has been resolved in the new version [7][8] - Additionally, issues with multilingual outputs, particularly in translating minor languages, have also been addressed, resulting in more coherent translations [9][10] Enhanced Capabilities - The model demonstrates improved programming and search capabilities, successfully simulating physical effects in programming tasks and providing comprehensive recommendations for plant care based on specific criteria [13][17] - The model's ability to cross-verify information and present it in a readable format has also been highlighted as a significant improvement [17] Future Outlook - The name "Terminus" suggests that this version may represent the culmination of the current technological path for DeepSeek, although future updates, including an Agent model, are anticipated by the end of the year [20][21]