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Model details

GLM-5.2 Caveman

GLM-5.2 Caveman is a compression-oriented variant of GLM-5.2, sharing the same upstream model while applying built-in instructions that favor shorter answers. It is intended for workflows where output length matters but explanations still need to retain technical substance, especially when preserving code, commands, error strings, numbers, API names, and important warnings.

The model’s practical distinction is stylistic compression rather than a separate output filter: rules direct it to retain validation, error handling, authentication, and content explicitly requested by the user. This makes it a fit for concise explanations, technical assistance, and applications that need lower verbosity without intentionally sacrificing critical implementation details. The compression is instruction-based, so shorter output is a strong tendency rather than a strict guarantee.

GreenPTglm-5.2-cavemanglm

Quick Info

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Provider
GreenPT
Model key
glm-5.2-caveman
Release date
Jun 13, 2026
Last updated
Jun 13, 2026
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$1.254
Output token cost
$5.016

Limits

Output tokens
131,072 tokens
Context window
1,000,000 tokens

Latest news about GLM-5.2 Caveman

GreenPT

Coverage

GreenPT announced (August 2026) that the Caveman output-compression ruleset, created by open-source builder Julius Brussee, is now available through the GreenPT API as part of its coding-model lineup. Caveman works at the language level rather than the model level: it instructs the agent to compress prose while preserv The blog frames Caveman as a response to the cost and energy overhead of verbose AI coding agents, noting that GPT-5-class models can cost $10–$15 per million output tokens and that each output token carries a hidden compute and electricity cost. By cutting wrapper prose without altering meaning, Caveman aims to make e

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