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摘要: AI & Enterprise
Z.ai unveils GLM-5.2 trained with only Huawei chips, without Nvidia
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Chinese AI company Z.ai, formerly Zhipu AI, unveiled its next-generation large language...
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AI & Enterprise
Z.ai unveils GLM-5.2 trained with only Huawei chips, without Nvidia
Generating...
AI Summary
Chinese AI company Z.ai, formerly Zhipu AI, unveiled its next-generation large language model GLM-5.2 trained without Nvidia chips, using only Huawei Ascend accelerators. Z.ai said the model delivered top-tier performance on coding and agent benchmarks, nearing Anthropic’s Claude Opus 4.8. It is distributed under the MIT licence without country restrictions, supports a 1 million-token context window and is priced below Claude Opus 4.8 for API use.
Jinju Hong
published 2026-06-19 09:22:35
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The core of GLM-5.2 lies not only in performance metrics but also in its training infrastructure and deployment approach. [Photo: Shutterstock]
[DigitalToday reporter Jinju Hong (홍진주)] Chinese artificial intelligence (AI) company Z.ai (formerly Zhipu AI) has unveiled its next-generation large language model (LLM) GLM-5.2 trained without Nvidia chips. Its performance is close to Anthropic’s top-end model, and it is drawing attention in the global AI market by touting advantages in cost and openness.
According to crypto media outlet Decrypt on June 18 (local time), Z.ai said GLM-5.2, which it recently unveiled, delivered top-tier performance globally on major coding and agent benchmarks.
On the FrontierSWE benchmark, which evaluates long-duration autonomous software development capability, GLM-5.2 scored 74.4. That is close to Anthropic’s Claude Opus 4.8 at 75.1 and ahead of GPT-5.5 at 72.6.
On SWE-bench Pro, which measures the ability to resolve GitHub issues, GLM-5.2 scored 62.1, surpassing both GPT-5.5 at 58.6 and the previous GLM-5.1 at 58.4.
Market interest is focusing not only on performance but also on the development environment. Z.ai said it trained GLM-5.2 using only Huawei’s Ascend AI accelerators. The company said no Nvidia hardware
采集时间: 2026-06-19 20:17:15
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