Alibaba Qwen 3.8 27B Model Targets Edge AI

In another sign that open model competition continues to heat up between Chinese and U.S. model makers, Alibaba Cloud introduced its latest variant of its flagship model, Qwen 3.8-27B.Released over the weekend under the Apache 2.0 license, the open-weight model is optimized for software engineering, reasoning and performing long-horizon tasks. Alibaba said the model can provide stronger autonomous planning and enable flexible control of reasoning, enabling users to control how deeply they want the model to reason and whether the context used to help the model reason is kept or deleted.Qwen 3.8 27B comes a few days after U.S. vendors Meta and Nvidia introduced their own new open models. The release intensifies the open model race between the U.S. and China while also reflecting the sustained push of AI to edge devices. Like Meta Muse Glimmer and Nvidia’s Nemotron 3.5 Lightning, the smaller 27B variant of Qwen -- whose most powerful model, Qwen 3.8-Max, with 2.4 trillion parameters, is 88 times bigger than Qwen 3.8 -- is designed to run locally on a laptop.Related:IBM, OpenAI Partner to Accelerate Enterprise AIThe drive to the edge highlights the trend that vendors are paying attention to how enterprises are closely tracking the cost of their use of AI models and aiming to reduce costs as much as possible.“Many companies are looking to gain a better understanding of their token spend, what they’re actually getting out of the model, the value proposition,” said Bradley Shimmin, an analyst at Futurum Group.Edge is About CostHe said that for many enterprises, it’s not easy to understand the costs of accessing frontier models using APIs. Meanwhile, running models locally enables enterprises to gain better control over the cost of the model's operations.“It’s really a way of applying FinOps, the idea of operationalizing the finances of AI,” Shimmin said. “Because of this renewed interest in observability and FinOps, we’re seeing these companies finetuning their spend.”Alibaba is also targeting the edge AI market because of the added benefits of its partnership with Apple. Alibaba will bring AI features to Apple devices sold in China. Therefore, having a model that can be used on edge devices helps Alibaba target Apple users in China.“All the Apple users in China will probably be using Qwen instead of Gemini, so there is a benefit in Qwen targeting this market because it has a large installed base,” said Lian Jye Su, an analyst at Omdia, a division of Informa TechTarget.The AI Open Source WarAlibaba competing directly against Meta with its Muse Glimmer open model is no surprise, given the success of Meta's previous open models, such as the Llama family, which became one of the most popular open model lines when it was released in 2023, Su added.Related:Lower Intro Price for Gemini 3.7 Flash to Attract Developers“There is an argument to be made that Meta can really do good open weight models,” Su said. “For Alibaba, Qwen is a very important way for them to market themselves. They want to continue to carry the open source mantle.”Moreover, Alibaba and other Chinese vendors have proven themselves to be drivers of open source over the past year, Shimmin said.He added that it is due to the release of multiple Chinese open models that Meta reversed course on its policy of releasing only open models, enabling the AI market to return to its original balance between open and closed, proprietary models --- the approach dominated by U.S. AI labs Anthropic and OpenAI.“The AI industry was built on the back of open source technologies,” Shimmin said. “The ideal of open source has an ecosystem-wide collaborative effort, not something that was locked down with IP containers opaque to users trying to understand, even the basics of why a model says what it does or how their spending is being utilized.”About the AuthorNews Writer, AI BusinessEsther Shittu has covered AI technologies and industry trends since 2021. As co-host of the Targeting AI podcast, she talks with experts, thought leaders and practitioners exploring critical AI developments. Before AI Business, she wrote for SearchEnterpriseAI, the New York Daily News, Bklyner and the Brooklyn Daily Eagle. When she's not diving deep into the world of AI, she spends her time on passion projects and raising her three daughters.