Zhipu AI has officially launched GLM-5, a next-generation open-source foundation model built for complex systems engineering and long-horizon agentic tasks.
Phala is proud to serve as an official deployment partner for this launch. We’re working side-by-side with the GLM team to validate the most effective production deployment setup—so GLM-5 can reach production-ready availability and real-world adoption as quickly as possible.
Our Role in Bringing GLM-5’s Power to Production
GLM-5 isn’t just an incremental upgrade—it represents a clear shift toward system-level intelligence and long-running agent execution. Instead of optimizing for short-form code generation, GLM-5 is designed for complex engineering workflows: planning across many steps, reasoning over large repositories, and executing tasks that require sustained context and alignment.
At Phala, we see this as the direction the industry is moving toward. Coding models are evolving from “writing code” to building systems, where agentic depth, architectural reasoning, and long-horizon execution matter more than surface-level output quality. GLM-5 is a strong signal that open source is entering this era as well.
Unlocking GLM-5’s Advanced Capabilities with Phala:
GLM-5 delivers a major leap in both scale and training infrastructure, expanding from 355B parameters to 744B, and increasing pre-training data from 23T to 28.5T tokens. It also integrates DeepSeek Sparse Attention (DSA) to significantly reduce deployment cost while preserving long-context capacity.
On the post-training side, Zhipu AI introduced slime, a novel asynchronous reinforcement learning infrastructure designed to improve RL efficiency at scale—enabling more fine-grained post-training iteration and contributing to GLM-5’s strong performance across reasoning, coding, and agentic workloads.
- Purpose-built for complex systems engineering and long-horizon agentic tasks
GLM-5 is designed to handle multi-stage, long-running workflows across frontend, backend, and large-repository environments. On CC-Bench-V2, it significantly outperforms GLM-4.7 across frontend, backend, and long-horizon tasks, narrowing the gap to Claude Opus 4.5.
- Scaled architecture with cost-efficient long context
GLM-5 scales from 355B to 744B parameters and increases pre-training data from 23T to 28.5T tokens. It integrates DeepSeek Sparse Attention (DSA) to reduce deployment cost while preserving long-context capacity.
- Advances in post-training and benchmark performance
Powered by slime, a novel asynchronous RL infrastructure, GLM-5 improves training efficiency and enables more fine-grained post-training iterations. It achieves best-in-class performance among open-source models across reasoning, coding, and agentic benchmarks, closing the gap with frontier systems.
Why GLM-5 Matters
GLM-5 is positioned as an open-source foundation model built for complex systems engineering and long-horizon agent workflows. It delivers production-grade productivity for large-scale programming tasks, with performance that continues closing the gap with frontier closed-source systems.
This direction reflects a broader industry shift: the most important coding models are no longer those that merely generate code, but those that can reason, plan, debug, refactor, and execute end-to-end engineering workflows. GLM-5 is one of the strongest open-source entries into this new phase.
About Phala
Phala is a confidential AI cloud platform that provides secure, private, and high-performance computing for AI models. Our mission is to enable developers to deploy AI models with enhanced privacy and security features, fostering trust and innovation in the AI space.
- GLM-5 confidential LLM : https://www.redpill.ai/models/z-ai/glm-5
- Use Phala GLM-5 on OpenRouter: https://openrouter.ai/z-ai/glm-5
About Zhipu AI
Zhipu AI is a leading artificial intelligence company focused on developing advanced foundation models and AI technologies. Through innovation and open-source contributions, Zhipu AI continues to empower developers and push the frontier of AI forward.
