China turns up the heat with open model blitz as US model makers panic

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China turns up the heat with open model blitz as US model makers panic

For the first time, Alibaba's Qwen team is letting its 'Max' model out of the API pen; meanwhile, DeepSeek V4-Flash gives new meaning to cheap and cheerful competition

Tobias Mann

Tobias<br>Mann

SYSTEMS EDITOR

Published<br>mon 3 Aug 2026 // 23:40 UTC

The AI arms race reached a fever pitch on Monday after Chinese e-commerce and cloud provider Alibaba called into question America’s technological lead with the launch of Qwen 3.8-Max, a 2.4 trillion-parameter model that goes toe-to-toe with the best models from Anthropic and OpenAI.<br>The new model comes just days after the launch of DeepSeek V4 Flash 0731, which, according to independent benchmarks by Artificial Analysis, performs within a single point of OpenAI’s budget-friendly GPT-5.6 Luna while costing 40 percent less per task. What’s more, at just 284 billion parameters, it’s small enough to run on relatively modest enterprise servers and workstations.<br>Chinese model devs like Moonshot, Alibaba, and DeepSeek are now attacking their American counterparts on both price and performance. The pincer movement comes as US model devs like Anthropic and OpenAI stoke fears over the origins and safety of China-made AI models.

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In a recent blog post, Anthropic CEO Dario Amodei insisted he’s not opposed to open models, just ones made in China, ones distilled from proprietary models, and ones that do not meet rigorous safety metrics. In other words, anything that actually competes with Anthropic's own models.

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The safety bit is particularly disingenuous, as the company’s fearmonger-in-chief has gone out of his way to stoke fears among US government officials. Proprietary models can be controlled, but open weights, once released in the wild, are impossible to claw back.<br>But neither Amodei’s comments nor commitments from major American and European tech giants change the fact that China is providing the only meaningful competition in the open weights arena.<br>China dominates here. Speaking on CNBC Monday, Clément Delangue, CEO of Hugging Face, the biggest and most influential model repo in the world, said as much.<br>“They’re clearly dominating on open models right now, and I wouldn’t be surprised if they start dominating at the frontier either by the end of this year or next year at the rate of progress,” he told the financial TV news network.<br>America’s most capable open weights model, Inkling, is just shy of a billion parameters, and still can’t keep up with DeepSeek’s finest. Models like Moonshot's Kimi K3 and Z.ai's GLM 5.2 are in an entirely different orbit.<br>In fact, an enterprise's only credible alternatives to proprietary models and their dubious security policies are Chinese models. DeepSeek, Alibaba, Moonshot, MiniMax, and Z.ai aren’t going to pass that opportunity up.<br>Alibaba lets its most powerful model loose on the world<br>Of the Chinese model devs, Alibaba is arguably the most like its American competition. Its open-weight models are well regarded, and their range of sizes and permissive licensing have made them attractive for fine-tuning application-specific systems. However, like Google and OpenAI, its top models have been locked behind an API – until now.

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Seizing the moment, Alibaba is making its most capable model weights available for download for the first time with the launch of Qwen 3.8-Max.<br>The blog post contains the usual array of vaguely intelligible bar charts showcasing how the model compares to OpenAI and Anthropic’s own models, as well as a slew of demos that would have made Billy Mays proud.

Alibaba's Qwen 3.8-Max blog post paints a very simple picture. Whatever OpenAI and Anthropic can do, it can do just as well, if not better, and for cheaper than the rest.<br>Image credit Alibaba

If you want specifics, we recommend checking out the launch blog here. You don’t have to look that closely to get what Alibaba is selling: anything OpenAI and Anthropic can do, we can do as well, if not better, cheaper, and on the hardware you own.<br>With that said, 2.4 trillion parameters is a rather big lift for most enterprises, likely requiring 48-64 Nvidia B200-class GPUs if deploying in a customer-facing capacity. For internal workloads, 8-16 B300 or AMD MI355X GPUs would be adequate.<br>If that’s a little rich for your blood, Alibaba hasn’t forgotten its roots and will be releasing a 27-billion parameter version of the model alongside the Max variant.<br>With benchmarks, model devs can usually find a collection of tests that paint their model in a positive light. And unsurprisingly, Artificial Analysis’ own Intelligence leaderboard tells a slightly different story than Alibaba’s, with Qwen 3.8-Max matching Anthropic’s less-capable, but still formidable, Claude Sonnet 5.

Artificial Analysis' Intelligence Benchmark doesn't paint the same glowing picture of Qwen...