GLM 5.2: 1M-Context Agentic Reasoning Model

GLM 5.2 is a 753B parameter Mixture-of-Experts model developed by Z.ai. It builds on GLM 5 with a sparse-attention design that supports a 1M-token context window, targeting long-horizon agentic tasks, large-codebase engineering, and advanced reasoning, with native English and Chinese support.

Key Features

• Frontier Reasoning - 99.2 on AIME 2026 and 91.2 on GPQA-Diamond
• Agentic Software Engineering - 62.1 on SWE-bench Pro for repository-level, multi-file tasks
• Tool Use - 40.5 on Humanity's Last Exam, rising to 54.7 with tool access
• 1M-Token Context - Long-document analysis, large-repo navigation, and extended agentic trajectories in a single context
• Interleaved Thinking - Reasons before every response and tool call; defaults to thinking mode
• Bilingual - Native English and Chinese language support

Use Cases

• Software engineering, code generation, and multi-file repository-level tasks
• Multi-step agentic workflows with tool calling and web browsing
• Complex mathematical reasoning and competition-level problem solving
• Long-context document analysis, synthesis, and generation
• Terminal-based development, operations, and systems administration
• Research tasks requiring extended browsing and context management

Architecture and Design

GLM 5.2 is a 753B parameter Mixture-of-Experts model that uses a sparse attention mechanism with IndexShare, reusing the attention indexer across every four layers to reduce the cost of long-context inference while preserving capacity across its 1M-token window. The design extends the GLM 5 architecture toward longer context and more reliable agentic behavior.

Training and Inference

GLM 5.2 builds on the GLM 5 foundation with refreshed post-training for stronger agentic coding and tool use. It defaults to thinking mode, reasoning before each response and tool call, and Z.ai recommends a temperature of 1.0 with top-p 0.95 for general reasoning tasks.

Deploy GLM 5.2 on Vast.ai for frontier-class agentic reasoning, coding, and long-context capabilities with flexible GPU infrastructure.