GLM 5

• 🆕 Z.ai's February 2026 flagship for agentic engineering and reasoning.
• 📏 744B-parameter MoE, 40B active, scaled up from GLM-4.5.
• 🧠 Trained on 28.5T tokens with new asynchronous RL infrastructure.
• 🔧 Adds DeepSeek Sparse Attention to cut training and inference cost.
• 📚 Large context window (catalog: 198K tokens), FP8 weights available.
• 🎯 Capabilities: reasoning, code-optimization, function calling, web search.
• 🔒 Released open-weight under the permissive MIT license.
• 💬 Vendor reports gains over GLM-4.7 across reasoning, coding, agentic tasks.

Z.ai

Z.ai, formally Knowledge Atlas Technology Joint Stock Co., Ltd., is a Chinese technology company specializing in artificial intelligence. Previously known internationally as Zhipu AI, the company rebranded to Z.ai in 2025. Its core focus is the GLM family of…

GLM 5 is the February 2026 flagship from Z.ai (formerly Zhipu AI), positioned for complex systems engineering and long-horizon agentic work. Architecturally it is a Mixture-of-Experts model with 744 billion total parameters and roughly 40 billion active per token, scaled up from GLM-4.5's 355B (32B active), with pre-training data expanded to 28.5 trillion tokens. It is distributed open-weight under the MIT license in both full-precision and FP8 formats.

The two headline changes over earlier generations are efficiency-focused. GLM 5 adopts DeepSeek Sparse Attention (DSA), which the technical report describes as dynamically allocating attention by token importance to lower compute without compromising long-context understanding — an advance over the standard MoE used in GLM-4.5. Post-training uses a new asynchronous reinforcement-learning infrastructure built on the "slime" framework that decouples generation from training to improve GPU utilization.

Relative to its same-family predecessor GLM 4.7, Z.ai reports significant improvements across academic benchmarks in reasoning, coding, and agentic tasks.

GLM 5 was followed by refreshed siblings GLM 5.1 and GLM 5.2, the latter extending to a roughly 1M-token context with the IndexShare architecture.