# Alibaba pitches AI as 'work-mate' to win over users > Source: > Published: 2026-08-04 02:36:42+00:00 It was just last year that DeepSeek emerged as China's first serious contender in the global AI race. Since then, a wave of Chinese labs has quietly raised the stakes, churning out bigger, cheaper, more efficient models that are giving US rivals a run for their money. Alibaba just did it again. On Sunday, Alibaba launched Qwen3.8-Max, a 2.4 trillion-parameter model that the company is calling not only its biggest model, but also its most capable in the Qwen family. The model touts upgrades across coding, agentic use cases, long-horizon tasks, research, and other complex tasks. The company's promotional video focuses on Qwen3.8's ability to act as an "always on work-mate," showing examples of it doing hours worth of work while the worker can do more enjoyable tasks. For instance, one vignette shows Qwen3.8-Max designing chips nonstop for 12 hours while the engineer goes fishing. Another shows a biology professor playing tennis while the model verifies a protein. This approach, which contrasts with US labs by emphasizing the lifestyle users can reclaim, is garnering attention on [socials](https://x.com/MatthewBerman/status/2084099457474597222?s=20). It's anchored on the idea that the model sets a new bar for coding and coworking, a claim the benchmarks are meant to support. Qwen3.8-Max performed comparable to, or even higher than, leading models in a series of benchmarks Alibaba published. That included Anthropic's Fable 5, a model so powerful that the US temporarily banned it, and Kimi K3, a model with 2.8 trillion parameters that made headlines last month for its claim that it could outperform Anthropic, OpenAI, Google, and others. Since benchmarks aren't always the truest indicators of performance in real-world tasks, more notable is its performance on crowdsourced, independent benchmarks such as the Code Arena for front-end web development tasks, where it placed fourth following Claude Opus 5, Kimi K3 Max, and Claude Opus 5 High. Another noteworthy aspect of the release is the models' cost, which, based on current pricing across the frontier field, Qwen3.8-Max's rates ($2 input / $6 output per million tokens) land on the cheaper end (by comparison, Fable costs $10 per million tokens for input and $50 for output). This is likely to further the price war that is already heating up in the US, with Chinese labs wielding both benchmark performance and token economics as powerful competitive forces. Alibaba plans to release the open weights of Qwen3.8-Max next week, another differentiator from the leading US labs. Regardless of the benchmark results, Andrew Yoon, technical staff member at CivAI, maintains that the US still holds the lead. "Claims that recent Chinese models match or beat the US frontier are overstating cherry-picked benchmark results," said Yoon. "This isn’t to say that the models are weak. Models like Qwen 3.8 Max, Kimi K3, and GLM 5.2 are all very capable, but they continue to lag the US frontier by a significant margin." ## Our Deeper *View* Alibaba's latest release not only adds to the onslaught of highly capable, efficient, and inexpensive models coming out of China, but also highlights a different approach than the US labs on multiple fronts. The most obvious parallels are the same strengths seen in the releases of Kimi K3 and the DeepSeek models: cheaper, open-weight models that don't compromise on performance. The more interesting angle, however, is the focus on giving people back their time rather than simply increasing productivity, which is what US labs have focused on until now. While this framing may strike some as tone-deaf, given the very real concerns about AI displacing jobs by doing people's work for them, it's an interesting approach that might actually appeal to the emotions of people in the broader public, who tend to be very skeptical of AI. If the US adopted more of a [Chinese marketing approach](https://x.com/jenzhuscott/status/2084124205571076379?s=20), I'd be curious to see whether it would bring more people on board with using the technology.