9月22日云栖大会杭州开幕，阿里公布大模型进展：Qwen4已投入训练，后续参数规模计划扩至5万亿至10万亿；递归自我改进进入训练、推理及芯片协同；多模态矩阵升级，11月发布新一代视频生成模型。刘大一恒称Scaling是迈向ASI的重要路径。
阿里通义千问团队近日开源全新多模态MoE模型Qwen3.8-Flash-Next，作为Qwen4架构早期预览版。该模型采用高度稀疏的混合专家设计，总参数1250亿，另搭配510亿参数N-gram嵌入表和40亿参数多token预测模块，以极低计算开销实现越级性能表现。
阿里千问发布多模态MoE模型Qwen3.8-Flash，并开源下一代架构Qwen3.8-Flash-Next（Qwen4雏形）。模型总参数125B，搭载51B N-gram Embedding，每token仅激活6B；原生支持26万token，可扩展至100万。训练成本为前代1/9，API定价输入每百万Tokens 1元、输出3元。
Alibaba
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输入tokens/百万
输出tokens/百万
上下文长度
$4
$16
1k
$1
$10
256
$2
$20
$6
$24
$8
$240
52
$3.9
$15.2
64
$15.8
$12.7
$0.8
128
$54
$163
32
$1.6
$0.75
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