SynopsisQwen3.8-Flash supports a default context window of 262,144 tokens, expandable to 1 million tokens, enabling it to handle large files, lengthy conversations and extensive research materials. It also released open-source weights for Qwen3.8-Flash-Next, allowing the developer community to evaluate an architecture that Qwen said would serve as a prototype for its next-generation Qwen4 model family.ReutersAlibaba's Qwen has released a new multimodal model, Qwen3.8-Flash, that delivers stronger coding and office-task performance while cutting training costs, it said in a statement on Wednesday published on social media.As ecommerce growth stagnates, AI has become the biggest driver of revenue growth for the Chinese e-commerce and cloud computing giant.Its Qwen AI models are some of the most popular in China, where competition is intensifying in the sector.Qwen3.8-Flash supports a default context window of 262,144 tokens, expandable to 1 million tokens, enabling it to handle large files, lengthy conversations and extensive research materials.Compared with its previous Qwen3.7-Plus model, Alibaba said it requires about one-ninth of the training cost.Qwen said it would charge 1 yuan ($0.1488) per million input tokens and 3 yuan per million output tokens for access through its application programming interface.It also released open-source weights for Qwen3.8-Flash-Next, allowing the developer community to evaluate an architecture that Qwen said would serve as a prototype for its next-generation Qwen4 model family.On Sunday, Alibaba launched a heavily discounted HK$80-billion share sale to fund its AI ambitions. ($1 = 6.7220 Chinese yuan renminbi) ...moreElevate your knowledge and leadership skills at a cost cheaper than your daily tea.Subscribe Now
Alibaba's Qwen launches Qwen3.8-Flash AI model with lower training costs - The Economic Times
Qwen3.8-Flash supports a default context window of 262,144 tokens, expandable to 1 million tokens, enabling it to handle large files, lengthy conversations and extensive research materials. It also released open-source weights for Qwen3.8-Flash-Next, allowing the developer community to evaluate an architecture that Qwen said would serve as a prototype for its next-generation Qwen4 model family.











