小鵬汽車在2026全球新品發佈會上宣佈，將“物理AI”與“全球化”定爲年度核心戰略，標誌着公司從技術探索轉向實踐應用。物理AI技術將全面落地並實現規模化量產，同時公佈了跨時代的產品交付計劃。
微軟研究院推出深度學習交換-關聯泛函Skala，顯著提升Kohn-Sham密度泛函理論計算效率。該模型通過模擬非局部效應，在保持與meta-GGA相當速度的同時，達到混合泛函精度水平。測試顯示：W4-17分子體系原子化能量評估平均絕對誤差僅1.06kcal/mol，單參考子集誤差更降至0.85kcal/mol，GMTKN55基準測試表現優異。
硅基流動平臺上線螞蟻百靈團隊開源的Ling-mini-2.0模型。該模型採用MoE架構，總參數量16B，但每個Token僅激活1.4B參數，在保持高性能的同時顯著提升生成速度，實現了小體量與大能量的突破。
谷歌發佈AI環境影響研究，提出“全棧”方法評估Gemini模型能耗。數據顯示，Gemini處理文本提示僅消耗0.26毫升水和0.24Wh能量，排放0.03克二氧化碳。谷歌稱2024年5月至2025年5月期間，每次排放總量減少44倍。
Google
$0.49
輸入tokens/百萬
$2.1
輸出tokens/百萬
1k
上下文長度
Openai
$2.8
$11.2
Xai
$1.4
$3.5
2k
$7.7
$30.8
200
-
Anthropic
$105
$525
$0.7
$7
$35
$17.5
$21
Alibaba
$1
$10
256
$6
$24
$2
$20
$4
$16
Baidu
128
Bytedance
$1.2
$3.6
4
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