Two Chinese AI models are reportedly claiming to rival heavyweights like OpenAI and Anthropic, ramping up pressure on Silicon Valley to face the competition.
Alibaba said its new model, built with 2.4 trillion parameters, delivers stronger performance in coding, reasoning and AI agent tasks. This came following Moonshot’s release last week of Kimi K3, a 2.8-trillion-parameter open-weight model designed for software engineering and autonomous task execution.
Alibaba said Qwen3.8-Max outperformed OpenAI’s GPT-4.1 and Google’s Gemini 2.5 Pro on several benchmarks while approaching Anthropic’s Claude Opus 4.1 in coding-related evaluations, although those results have not been independently verified. The company is integrating the model into Alibaba Cloud and its AI coding tools as it expands enterprise applications.
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Meanwhile, Moonshot highlighted Kimi K3’s performance across coding, reasoning and agent benchmarks. Built on a mixture-of-experts architecture, the company said the model delivers competitive performance while reducing inference costs compared with similarly sized dense models.
“K3 represented another instance where the ability of China’s top AI labs to keep pace with the US frontier has surprised global investors,” Bernstein analysts led by Robin Zhu wrote in a Friday note.
Chinese AI models are gaining traction among Western countries. U.S. lawmakers are considering how to curb the growing adoption of Chinese AI models by homegrown companies.
The reaction to Chinese models has been compared to the hype following the launch of DeepSeek last year.
Patrick Moorhead, the CEO and chief analyst at Moor Insights and Strategy, characterized the market’s reaction to the new Kimi K3 model as “an over-reaction shockingly similar the DeepSeek panic,” explaining in a post on X that despite the technology’s advances, “We are far away from super-intelligence.”
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Moorhead said in the post that large language models, or LLMs, like Kimi K3 will only “accelerate and grow the inference market faster than without,” underscoring a general shift in the tech sector from merely focusing on the size and presumed capabilities of a model by itself to the overall application that the technology powers.
Perplexity CEO Aravind Srinivas told CNBC last week that there’s more focus from startups and developers to figure out the best methodologies for using AI models that can power their apps, instead of squarely focusing on one gigantic, underlying system.
“The model alone is no longer the product,” Srinivas said at the time. “It is the harness, the orchestration system that puts the model inside a very capable harness and pairs the model with a lot of tools.”