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Model details

GLM-4.6

GLM-4.6 is a frontier-scale model built on a 355-billion parameter Mixture-of-Experts architecture. Designed to serve as a versatile engine for complex agentic workflows, it excels in tasks requiring deep reasoning, real-world coding, and long-context processing. By expanding its context window to 200,000 tokens, the model is engineered to handle extensive information exchanges, making it particularly effective for developers building sophisticated coding agents, automated frontend generation, and search-based applications that require high-level logical coherence.

The model represents a significant shift in accessibility for high-performance AI, as it is released under a permissive MIT license. This design choice allows enterprises to self-host, deeply customize, and integrate the model into proprietary infrastructure without vendor lock-in. Beyond its core architecture, the model has been refined to align closely with human preferences in style and readability, ensuring natural performance in role-playing and writing scenarios. Its combination of frontier-level coding benchmarks and efficient token usage positions it as a practical, scalable solution for organizations seeking to own their AI stack while maintaining competitive performance against leading international models.

ModelScopeZhipuAI/GLM-4.6glm

Quick Info

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Provider
ModelScope
Model key
ZhipuAI/GLM-4.6
Release date
Sep 30, 2025
Last updated
Sep 30, 2025
Knowledge cutoff
2025-07
Input modalities
Output modalities
Capabilities

Cost

A provider subscription or plan supersedes token-based pricing for this model.

Limits

Output tokens
98,304 tokens
Context window
202,752 tokens

Latest news about GLM-4.6

Zhipu AI

CoverageAnalysis

Cirra AI published a technical analysis on October 18, 2025 focused on GLM-4.6's tool calling and MCP (Model Context Protocol) capabilities. It describes GLM-4.6 as Zhipu AI's latest flagship mixture-of-experts language model explicitly designed for agentic tasks, featuring a 200K-token context window, a reasoning-capa The article notes that GLM-4.6 builds on GLM-4.5's native function-calling foundation and explicitly supports tool use during inference, autonomously deciding when to invoke external tools such as web search, calculators, or code execution. It reports near-parity with Claude Sonnet 4 at a 48.6% win-rate on multi-turn c

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