AI Models in China have evolved rapidly over the past few years. After a period dominated by larger models and stronger benchmark performance, companies are beginning to focus on new priorities.
Recently, Xiaomi introduced MiMo-V2.5-Pro-UltraSpeed. The launch attracted significant attention. According to the company, more than 66,000 users requested access within two weeks. More importantly, the market focused on the model’s inference speed rather than its overall size.
As a result, this trend suggests that companies are starting to evaluate AI Models in China in a different way.
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Competition Between AI Models Is Changing
For several years, companies mainly competed by increasing model size and improving benchmark results.
They successively introduced models with hundreds of billions and even trillions of parameters. At the same time, benchmark rankings became an important way to measure performance.
However, enterprise demand is changing as artificial intelligence moves into real business environments.
Today, companies no longer look only for powerful models. Instead, they want solutions that deliver better efficiency in practical applications.
Consequently, AI Models in China are no longer judged solely by benchmark performance. Companies now value practical efficiency just as much.
Why Is Efficiency Becoming More Important?
Today, AI supports industries such as finance, logistics, manufacturing, and customer service.
These sectors process large amounts of information every day. Therefore, faster responses can directly improve productivity while reducing operating costs.
This explains why MiMo-V2.5-Pro-UltraSpeed has attracted so much attention. According to Xiaomi, the model can process more than 1,000 tokens per second, with peak speeds approaching 1,200 tokens.
To achieve this performance, Xiaomi uses a MoE architecture that activates only the parameters required for each request.
In addition, the company combines technologies such as FP4 quantisation, DFlash speculative decoding, and the TileRT inference engine. Together, these optimisations increase speed while keeping computing costs under control.
When Speed Becomes a Competitive Advantage
Today, companies no longer compete only by building larger models.
Instead, they aim to balance performance, speed, and operating costs. In many situations, a faster model delivers more value than one that offers only slightly better benchmark results.
This shift is reshaping the entire market. DeepSeek, Alibaba’s Tongyi, Tencent’s Hunyuan, and Xiaomi’s MiMo all explore different ways to improve model efficiency.
As a result, speed is becoming a key competitive advantage. It improves the user experience while making large-scale AI deployment more practical for businesses.
Xiaomi’s latest model also highlights changing market expectations. As performance differences between leading models become smaller, companies increasingly value operational efficiency and faster execution.
Looking ahead, competition among AI Models in China will depend not only on technical capabilities but also on the business value companies can deliver.
Understanding the Evolution of AI Models in China
STAiiRS closely follows the development of AI Models in China, advances in AI inference, and the latest innovation trends to help international businesses better understand China’s AI market.
As enterprise demand continues to grow, companies increasingly prioritise efficiency, speed, and practical applications. These factors are likely to drive the next stage of development for AI Models in China.
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