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Chinese artificial intelligence groups have been rushing out model updates before the lunar new year holiday, as the world wakes up to the sector’s major advances led by start-up DeepSeek in the face of US chip restrictions.
On Monday, the eve of China’s most important annual holiday, the Hangzhou-based company released a new open-source model for image generation, cementing its reputation as the disrupter-in-chief in a field previously dominated by US giants. It came hot on the heels of model releases from tech giant Alibaba and start-ups Moonshot and Zhipu.
“This is the equivalent of dropping a massive release on Christmas Eve. We’ve all been working overtime to get stuff out before the holiday,” said one product manager at a large language model start-up.
While DeepSeek’s achievement has prompted panic in the US about the advances Chinese labs are making on bootstrapped budgets, industry insiders say it is feeding into a newfound “confidence” in China that will spur investment.
“DeepSeek has made faster progress than the other Chinese model companies. But this is giving them confidence that they can catch up,” said one AI investor in China.
DeepSeek has captured the world’s attention with a series of model releases that show similar performance to those of US rivals such as OpenAI and Meta, even though it claims to have a fraction of the computing resources and is blocked from acquiring the latest Nvidia processors by US export restrictions. Last week, it released its R1 reasoning model, an advanced model that rivals OpenAI’s o1 and can automatically learn and improve itself without human supervision.
“DeepSeek has injected a lot of energy into China’s AI players and, more broadly, into the global open-source AI community that will use its findings from its R1 paper to make progress on reasoning models,” said Wang Tiezhen, an engineer at AI research hub Hugging Face.
This week, investors dumped AI-related stocks, with Nvidia losing almost $600bn in market value on Monday. They were reacting to Chinese breakthroughs that show it is possible to build powerful models while pursuing a different strategy to the US one of building ever-larger computing clusters to get ahead in the AI race.
On Monday, Alibaba’s Qwen released Qwen2.5-1M, a series of new models that are capable of handling longer inputs, an important development that would mean the model could be deployed for AI agent applications with higher memory demands, according to Wang.
On the same day, DeepSeek released Janus-Pro, a text-to-image generation model that it claims can surpass state of the art ones from competitors such as OpenAI’s Dall-E 3 and Stability AI’s Stable Diffusion 3 on some benchmarks.
Zhipu, valued at its last funding round in December at $3bn, last week released an update to GLM-PC. The AI agent model is aimed at enterprise customers, enabling computers to automatically complete tasks such as filling out forms or digesting financial reports.
While Zhipu has not courted much attention for its LLM development, it has a lead among local AI start-ups in commercialising its technology, with support from local governments and state-owned enterprises that have partnered with the Beijing-based company to deploy its models.
Last week, another Beijing-based start-up Moonshot, which owns the popular AI chatbot Kimi, updated its reasoning model to Kimi k1.5, demonstrating strong results compared with established AI models for complex reasoning tasks. The latest release can process texts and images while handling long and complex queries.
It is standard practice for Chinese tech companies to release products before the long holiday, with the added benefit that potential customers with lots of free time during the break can test and explore them.
Once Chinese AI players return from their break, the race is on to become the leading player developing AI applications for commercial use. “If AI agents can create dramatic commercial value, one or two of the LLM players have a chance to transform into a new generation of software companies,” the AI investor said.
