9月22日雲棲大會杭州開幕，阿里公佈大模型進展：Qwen4已投入訓練，後續參數規模計劃擴至5萬億至10萬億；遞歸自我改進進入訓練、推理及芯片協同；多模態矩陣升級，11月發佈新一代視頻生成模型。劉大一恆稱Scaling是邁向ASI的重要路徑。
阿里通義千問團隊近日開源全新多模態MoE模型Qwen3.8-Flash-Next，作爲Qwen4架構早期預覽版。該模型採用高度稀疏的混合專家設計，總參數1250億，另搭配510億參數N-gram嵌入表和40億參數多token預測模塊，以極低計算開銷實現越級性能表現。
阿里千問發佈多模態MoE模型Qwen3.8-Flash，並開源下一代架構Qwen3.8-Flash-Next（Qwen4雛形）。模型總參數125B，搭載51B N-gram Embedding，每token僅激活6B；原生支持26萬token，可擴展至100萬。訓練成本爲前代1/9，API定價輸入每百萬Tokens 1元、輸出3元。
Alibaba
$1
輸入tokens/百萬
$10
輸出tokens/百萬
256
上下文長度
-
$6
$24
$2
$20
$4
$16
1k
$8
$240
52
$15.8
$12.7
64
$3.9
$15.2
$0.8
128
$54
$163
32
$1.6
$0.75
%20--%3e%3cdefs%3e%3cstyle%3e%20.st0%20{%20fill:%20%23061b40;%20}%20.st1%20{%20fill:%20%23306af1;%20}%20.st2%20{%20fill:%20%235ce5cf;%20}%20%3c/style%3e%3c/defs%3e%3cg%3e%3cpath%20class='st0'%20d='M55,10.5h9v3h-9v9h12V7.5h-12v3ZM64,19.5h-6v-3h6v3Z'/%3e%3cpolygon%20class='st0'%20points='69%2016.5%2078%2016.5%2078%2019.5%2069%2019.5%2069%2022.5%2081%2022.5%2081%2013.5%2072%2013.5%2072%2010.5%2081%2010.5%2081%207.5%2069%207.5%2069%2016.5'/%3e%3cpolygon%20class='st0'%20points='95%2010.5%2095%207.5%2083%207.5%2083%2022.5%2095%2022.5%2095%2019.5%2086%2019.5%2086%2016.5%2095%2016.5%2095%2013.5%2086%2013.5%2086%2010.5%2095%2010.5'/%3e%3cpath%20class='st0'%20d='M40,1.5v21h11.6l1.4-1.4v-7.6h0c0,0-1.4-1.5-1.4-1.5l1.4-1.4V2.9l-1.4-1.4h-11.6ZM50,19.5h-7v-6h7v6ZM50,10.5h-7v-6h7v6Z'/%3e%3c/g%3e%3cpath%20class='st1'%20d='M23.1,24L14.7,4.8l-4.9,11.2h3.8l-1.8,4H3.3L12.1,0H2C.9,0,0,.9,0,2v20c0,1.1.9,2,2,2h21.1Z'/%3e%3cpath%20class='st2'%20d='M34,0h-16.8l10.6,24h6.2c1.1,0,2-.9,2-2V2C36,.9,35.1,0,34,0ZM32.5,20h-4V4h4v16Z'/%3e%3c/svg%3e)
VIP會員
