GLM 5.3 open-weight model launches on Amazon Bedrock for coding and agentic tasks
Z.ai's GLM 5.3 is now available on Amazon Bedrock, according to an AWS blog post. The 753B-parameter mixture-of-experts open-weight model is optimized for coding and long-horizon agentic tasks, and Z.ai reports a leading CyberGym score of 84.5 for defensive security work. Bedrock offers managed APIs, cross-Region inference, prompt caching and service tiers, with access currently limited to eligible enterprise customers.
It gives enterprises a managed route to a strong open-weight coding and agentic model without operating their own inference stack, though the benchmark results remain vendor-reported.
Coding and agentic workloads are asking more of AI models than ever: refactor a repository spanning hundreds of files, sustain a multi-hour agentic workflow without losing context, and reason through complex systems problems with tool use at every step. Meeting those demands with open-weight models has historically meant provisioning and operating your own inference infrastructure.
GLM 5.3 from Z.ai (Zhipu AI) is now available on Amazon Bedrock. GLM 5.3, as published on Hugging Face Hub, is a 753B-parameter mixture-of-experts model optimized for coding and long-horizon agentic tasks. In particular, Z.ai has reported the model shows notable cyber security capabilities. On Amazon Bedrock, you can now use it through fully managed APIs with cross-Region inference, prompt caching, and service tiers. You don’t manage any infrastructure. Access to GLM 5.3 on Bedrock is available to eligible enterprise customers.
In this post, we show you how to invoke GLM 5.3 on Amazon Bedrock using the OpenAI-compatible APIs and reduce cost and latency with prompt caching. We then put the model to work in a realistic agentic workflow: running an authorized security test of your own application with Strix, an open-source AI penetration testing agent.
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