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Model details

GLM-5.2 (Z AI)

GLM-5.2 is Z.ai's flagship foundation model, released by the Chinese company Zhipu as a major step forward from GLM-5.1, with explicit emphasis on long-horizon tasks and complex agentic workflows. It is positioned as an open model that fits into existing developer environments, integrating directly with coding tools such as Claude Code, Cline, OpenCode, and OpenClaw. Z.ai describes it as a foundation model purpose-built for software engineering automation, sustained reasoning across extended trajectories, and workflows that span planning, implementation, and verification stages.

The model's defining technical characteristic is its very large usable context window, designed not merely to hold more tokens but to maintain stable performance through long, complex sequences. It introduces flexible thinking effort levels that let developers trade off reasoning depth against latency and compute, and it pairs this with full agent capabilities including function calling, structured JSON output, context caching, and MCP support for connecting external tools and data. Z.ai also highlights architectural improvements such as IndexShare, a technique aimed at reducing per-token compute requirements, making the model well suited to refactoring, API migration, cross-language work, and other project-scale engineering tasks.

LLM Gatewayzai/glm-5.2glm

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Provider
LLM Gateway
Model key
zai/glm-5.2
Release date
Jun 13, 2026
Last updated
Jun 13, 2026
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$1.40
Output token cost
$4.40

Limits

Output tokens
128,000 tokens
Context window
1,000,000 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about GLM-5.2 (Z AI)

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Coverage

Z.ai launched GLM-5.2, its latest flagship model designed for long-horizon tasks and complex agentic workflows. According to Pulse 2.0's coverage, GLM-5.2 supports a 1 million-token context window intended for handling large codebases, extended workflows, and project-level software engineering. Z.ai described GLM-5.2 a The Pulse 2.0 report also covers GLM-5.2's architectural changes, including the IndexShare technique aimed at lowering per-token compute at long context lengths and an improved multi-token prediction layer for speculative decoding to boost acceptance length and inference efficiency. Z.ai reported benchmark gains over G

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