Chinese firms are rapidly releasing competitive open-source large language models, often trained on domestic hardware, offering low-cost alternatives to US models and reshaping the global AI race.
With GLM-5.2, Z.ai heats up the global AI race, taking aim at Western leaders. The move highlights China's push to build competitive LLMs and puts the spotlight on data sovereignty as a driver for on-premise deployment decisions.
Shanghai Orient Computing Core Technology, founded by a Tsinghua-schooled chip industry veteran, is developing 3D AI processors to reduce China’s reliance on foreign GPUs. The move comes amid US export restrictions and the race for technological sove...
The Chinese company is bringing its LLM inference and training accelerators to the South Korean market, traditionally tied to the GPU ecosystem. The move widens hardware options for those seeking on-premise inference and fine-tuning stacks outside th...
Z.ai has released GLM-5.2, ranking fourth in performance benchmarks, with coding and agentic capabilities close to market leaders. Its cost is a fraction of Anthropic or OpenAI, raising questions about how this will influence deployment choices, espe...
Meituan has announced LongCat-2.0, a 1.6-trillion-parameter Large Language Model, entirely trained on hardware developed in China. The company emphasizes that this initiative represents a direct response to US export controls, highlighting China's gr...
Huawei has open-sourced OpenPangu-2.0-Flash, a Large Language Model with 92 billion total parameters (6 billion active) and a 512K token context window. The release of weights, inference code, and training operations provides new opportunities for on...
LongCat-2.0, a Large Language Model based on a Mixture of Experts (MoE) architecture with a total of 1.6 trillion parameters (approximately 48 billion activated per token), has been unveiled. Previously known as 'owl-alpha' on Openrouter, the model r...
