Zhipu's New Model Hits 490 tokens/s!

Zhipu AI has launched a new model in the GLM series, achieving an inference speed of 490 tokens/s and delivering a notable improvement in text generation efficiency. This speed metric means the model can provide faster output experiences in scenarios such as conversational responses and content generation.

Inference speed is one of the key metrics in the real-world deployment of large models. A higher tokens/s rate means shorter user wait times and the ability to serve more concurrent requests under the same hardware conditions, directly impacting inference costs and user experience.

As a representative company in China's large model space, Zhipu's GLM series has already garnered some attention in the open-source community. This speed optimization may involve technical approaches such as model architecture adjustments, inference engine optimization, or quantization and compression, though the specific implementation details remain to be disclosed.

Against the backdrop of increasingly fierce competition among large models, inference efficiency has become an important dimension for companies to differentiate themselves. Beyond parameter scale and training data, how to achieve more efficient inference under limited computing power is becoming one of the core challenges in deploying large models.

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