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Article
Flash

first_img Anthropic: Zhipu GLM-5.3 has end-to-end network utilization capabilities

On September 29, 2026, the Anthropic Frontier Red Team published a research article authored by Andrew Fasano, Marius Fleischer, Cole McFaul, Robert Xiao, and Tripp Gallagher. The article states that about five months ago, Anthropic released the Claude Mythos Preview through Project Glasswing in a limited manner, as it can autonomously construct end-to-end exploit capabilities; trusted defenders discovered over 10,000 vulnerabilities in critical software based on this, and similar capabilities have now spread to other models.The article mentions that the GLM-5.3 developed by ZhiPu AI (known overseas as Z.ai) is similar to the Claude Mythos Preview, possessing strong autonomous end-to-end exploit development capabilities, but it is released with open weights and lacks meaningful abuse restrictions. In simulated tests, the success rate of bypassing GLM-5.3 defenses using simple methods was about 64% to 100%, while the same methods failed to make the protected Claude model perform harmful tasks; these capabilities can also be used by defenders to strengthen systems.On September 17, 2026, the National Institute of Standards and Technology's Artificial Intelligence Standards and Innovation Center assessed that GLM-5.3 is currently the most powerful open-weight model in terms of network capabilities, lagging behind the U.S. frontier by about four months in its network benchmarks, and Anthropic stated that the capability conclusions are generally consistent.

Zhipu has launched and open-sourced the "Niu Lai" model GLM-5.3-Flash

Zhipu officially announced the launch and open-sourcing of GLM-5.3-Flash, which is the first native multimodal model in the GLM-5 series.It is reported that the overall performance of GLM-5.3-Flash exceeds that of GLM-5.2, with programming and Agent evaluations approaching Claude Opus 4.8, but at only one-tenth the price of GLM-5.2. It also features a new foundational model, introducing a mixed architecture of sparse attention and linear attention for the first time in the main GLM series, and is pre-trained with 30T Token multimodal data.Zhipu stated that to gather extensive and professional feedback from a wide range of users, large-scale testing was conducted with the anonymous model Ox-Alpha (referred to as "Niu Lai" in the Chinese community) on OpenCode and OpenRouter before the official release. Ox-Alpha quickly became the most popular model of the week, setting a new high for call volume on both platforms, with all request traffic supported by domestic chip computing power.Previously, the community's DeepSWE small sample test for Ox Alpha once achieved 80%, but that was based on only 10 questions. After expanding the sample, the score fell back to about 63%, and testers also actively corrected the initial claim. This score still belongs to the top tier, but is not as exaggerated as the initial 80%. After the weights are open-sourced, developers can directly deploy using frameworks like vLLM, SGLang, KTransformers, without needing to go through the anonymous model's API.
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