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Zhipu Launches GLM-5.1 High-Speed API, GLM-5.1-highspeed

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88Z AI, 22 May — Zhipu Open Platform has released the GLM-5.1 High-Speed API, achieving an output speed of 400 tokens/s and setting a new global benchmark for large model API speed. Jointly launched by Zhipu and the TileRT team, it combines flagship capabilities with ultra-low latency. It is suitable for high-demand scenarios like AI coding and real-time interaction, and is now available to select enterprise clients.

At a glance

  • GLM-5.1 High-Speed API reaches 400 tokens/s, setting a new global record
  • Jointly launched by Zhipu and TileRT, balancing flagship capabilities with low latency for select enterprises
Cover image for Zhipu Launches GLM-5.1 High-Speed API, GLM-5.1-highspeed
Cover image for Zhipu Launches GLM-5.1 High-Speed API, GLM-5.1-highspeed

The update

Zhipu Open Platform has officially launched the GLM-5.1 High-Speed API (GLM-5.1-highspeed), with a model output speed reaching 400 tokens/s, thereby setting a new global record for large model API speed. This breakthrough was achieved jointly by Zhipu and the TileRT team, marking the first time a domestic large model has combined flagship-level intelligence with ultra-low latency. This version is designed for applications highly sensitive to latency, such as AI programming assistance, real-time human-computer interaction, and real-time voice processing. By optimizing the underlying architecture, GLM-5.1-highspeed significantly reduces response time while maintaining high-performance output. Currently, the service is open to select enterprise clients, aiming to meet the strict dual demands for speed and quality in high-end business operations.

Sources & editorial note

This article is an AI-assisted synthesis by 88Z AI based on the public sources below. Product claims and availability are attributed to their publishers. It does not represent independent testing or first-hand reporting.

  1. 智谱开放平台Source published

Source dates above refer to the original announcements; the date under the headline is this article’s publication on 88Z AI.

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