GLM-5.2 is a GLM-family text foundation model developed by Z.AI and released on June 16, 2026. It is positioned for long-horizon coding and engineering tasks, with a 1M-token context window, 128K maximum output, and a reasoning_effort control for adjusting reasoning depth.
Key Features
1M Context Window: Supports up to 1M tokens of context for project-scale codebases, long documents, and multi-step engineering workflows.
Long-Horizon Coding: Z.AI reports 81.0 on Terminal-Bench 2.1 and 62.1 on SWE-bench Pro, with emphasis on project-level code understanding and sustained task execution.
Configurable Reasoning: Supports deep-thinking mode and the GLM-5.2-specific reasoning_effort parameter, with high and max reasoning levels for complex tasks.
Agent and Tool Integration: Supports function calling, streaming tool calls, structured output, context caching, and MCP-based tool/data-source integration.
Best Use Cases
Project-Scale Codebase Work: Reviewing, refactoring, migrating, or extending repositories where the model needs to retain architecture, module boundaries, API contracts, and engineering conventions.
Long-Horizon Engineering Tasks: Multi-file implementation, dependency-aware refactoring, SDK adaptation, debugging loops, and test-fix-verify cycles that require sustained progress.
Tool-Using Agent Workflows: Coding agents, internal automation, MCP-connected workflows, and structured-output systems that need reliable tool invocation and streamed tool-call arguments.
Capabilities and Limitations
Capability
Description
Reasoning
Supports deep-thinking mode and reasoning_effort; Z.AI positions it for complex engineering, debugging, and long-chain reasoning workflows.
Creative Writing
Supports general text generation through the chat completion API, but official GLM-5.2 materials emphasize coding and engineering use cases.
Coding
Z.AI reports Terminal-Bench 2.1 score of 81.0 and SWE-bench Pro score of 62.1, with focus on long-horizon coding-agent scenarios.
Multimodal
Text input and text output. Vision and multimodal workflows are handled by separate Z.AI models such as GLM-5V-Turbo.
Response Speed
Official docs do not publish latency or tokens-per-second figures; streaming responses and streaming tool calls are supported.
Context Window
1M tokens.
Max Output
128K tokens.
Tool Use
Function calling, streaming tool calls, structured output, context caching, and MCP integration.
Multilingual
Suitable for Chinese and English developer workflows; official docs do not publish a GLM-5.2 language coverage benchmark.
Known Limitations
Text-only model; image, video, and GUI-understanding tasks require a separate vision-language model such as GLM-5V-Turbo.
Very long contexts and 128K outputs can increase latency and cost; cap max_tokens and use context caching where applicable.
