Install GLM-OCR on Your PC Local Guide

If you want the fastest local installation for this model, use Docker.

Follow the sequence of steps detailed below.

The installer auto-downloads and deploys the entire model pack.

Once launched, the setup wizard will detect your specs to configure the model for maximum efficiency.

? File Hash: 7f2ab737095c7ff70a9fe362bdfec7d9 — Last update: 2026-06-23 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: high-speed DDR5 memory preferred for CPU offloading Disk: high-speed SSD 120 GB to cache model layers GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats

GLM-OCR is a lightweight vision-language model tailored specifically for advanced document understanding and structure preservation. The architecture integrates a 400M parameter CogViT visual encoder alongside a compact 500M parameter GLM language decoder to maximize layout analysis precision. Unlike classic character recognition engines, this framework introduces an innovative Multi-Token Prediction (MTP) loss mechanism to increase decoding throughput substantially while lowering system memory demands. It effortlessly reconstructs intricate multilingual tables, LaTeX formulas, and handwritten text into semantic Markdown or structured JSON outputs. The compact blueprint allows for highly accurate, state-of-the-art multi-page processing directly within resource-constrained edge computing environments.

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https://ukrpersonal.com/category/wrappers/