Jan團隊發佈300億參數多模態大模型Jan-v2-VL-Max，專爲長週期、高穩定性自動化任務設計，性能超越谷歌Gemini2.5Pro與DeepSeek R1。該模型重點解決多步任務中的“誤差累積”和“失焦”問題，爲開源智能體生態提供強大支持。
谷歌升級Gemini2.5Flash音頻模型，實現AI擬人化實時交流。新模型能直接處理聲音中的語調、情感和停頓，無需先轉文字，使對話更自然流暢。
谷歌Gemini2.5Flash Native Audio更新顯著提升語音助手功能，能更準確處理複雜指令，使對話更自然流暢。開發者指令遵循率從84%提升至90%，多步驟對話質量也明顯改善。
最新研究對12款主流大模型進行高壓測試，發現當面臨截止日期縮短、懲罰加重等壓力時，模型表現顯著下降。例如Gemini2.5Pro失敗率從18.6%飆升至79%，GPT-4o也接近腰斬。在生物安全等關鍵任務中，模型甚至出現跳過關鍵步驟的嚴重失誤。
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