GLM-5.3

An Interconnects open-artifacts roundup covers GLM-5.3 within a broader look at September 2026 open-model releases, including Motif-3 and Hy4-preview. The piece notes a trend in which Chinese frontier model makers are tightening licensing relative to their Western counterparts, citing Kimi K3's commercial-agreement req On GLM-5.3 specifically, the article documents Zhipu's shift away from the MIT license used for GLM-5.2 and earlier releases to a custom license. The new license requires that any Model-as-a-Service provider whose aggregate revenue (including undefined "affiliates") exceeds US$10 billion over any consecutive 12 months

Z.ai announced GLM 5.3 on August 14, 2026, as an open-weight model targeting advanced coding and cybersecurity work, built on the same base architecture as GLM 5.2 with all gains coming from expanded post-training. The company paired the release with OpenVuln, branded internally as "VulnHunter," a scanning service that Concerned about the dual-use implications of those capability gains, Z.ai said it would hold back GLM 5.3's public model weights for approximately two weeks after the August 14 launch, restricting initial access to a group of vetted security partners through its GLM Coding Plan and ZCode agent. The company acknowledged

An Apidog blog details self-hosting preparations for Z.ai's GLM-5.3, which shipped on August 14, 2026. GLM-5.3 is a post-training-only release on top of the unchanged GLM-5.2 base model, with Z.ai reporting a 50% coding gain over GLM-5.2 on its in-house Code Bench and a Terminal-Bench 3.0 jump from 4.6 to 28.3. The art The piece outlines the GLM-5 family architecture (MoE, ~744B total parameters, ~40B active, 200K context per Z.ai docs) and the resulting deployment footprint (roughly 1.5 TB at BF16, about half at FP8, before KV cache). It identifies vLLM and SGLang as the realistic day-one serving stacks, both exposing OpenAI-compati

A Data Science Collective analysis breaks down Z.ai's 16-benchmark GLM-5.3 launch table and notes that post-training alone took Terminal-Bench 3.0 from 4.6 to 28.3 while leaving the base model unchanged. The author finds the gains are uneven across benchmarks and that the cybersecurity row Z.ai leads with actually move On CyberGym, where models receive text descriptions of vulnerabilities and must reproduce them, GLM-5.3 scored 84.5 versus Claude Fable 5's 83.8 and GPT-5.6 Sol's 83.6, placing it at the top of that benchmark. However, on the two benchmarks requiring the model to build its own exploits, GLM-5.3 finishes behind both fro

China Daily's August 14, 2026 launch coverage reports that Zhipu AI (Z.ai) launched GLM-5.3, framing it as a next-generation foundation model with coding and AI agent capabilities approaching what the article calls "Claude Fable 5." Zhipu stated GLM-5.3 has 743 billion parameters and that its performance gains come fro According to the article, Zhipu positioned GLM-5.3 as the strongest open-source model across several mainstream benchmarks, with practical coding performance surpassing other Chinese models, and framed cybersecurity as an emerging battleground as AI agents grow more capable of identifying vulnerabilities and operating

InferenceX's model page provides a technical profile of GLM-5.3 alongside its predecessor GLM-5.2. GLM-5.3, announced August 14, 2026, reuses the GLM-5.2 base model entirely, with all gains attributable to post-training. It is positioned by Z.ai as "Frontier Coding with Emergent Cyber Capabilities," claimed as open-sou GLM-5.3 is text-only, always-reasoning, with a 1M-token context, 128K max output, and three effort levels (low, high, max; default max), and thinking can no longer be disabled. The page highlights a significant licensing shift: GLM-5.2 shipped under MIT open weights, while GLM-5.3 moves to a custom license with restric