GLM-5V-Turbo turns screenshots and design drafts into code
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Introducing GLM-5V-Turbo: Vision Coding Model - Native Multimodal Coding: Natively understands multimodal inputs including images, videos, design drafts, and document layouts. - Balanced Visual and Programming Capabilities: Achieves leading performance across core benchmarks for multimodal coding, tool use, and GUI Agents. - Deep Adaptation for Claude Code and Claw Scenarios: Works in deep synergy with Agents like Claude Code and OpenClaw. Try it now: https://t.co/WCqWT0qCQb API: https://t.co/xDy1O6ZPcz Coding Plan trial applications:
The model can understand design drafts, screenshots, and web interfaces to generate complete, runnable code, truly achieving the goal of "seeing the screen and writing the code."
GLM-5V-Turbo leads in benchmarks for design draft reconstruction, visual code generation, multimodal retrieval and QA, and visual exploration. It also performs exceptionally well on AndroidWorld and WebVoyager, which measure control capabilities in real GUI environments.
Regarding pure-text coding, GLM-5V-Turbo maintains stable performance across three core benchmarks of CC-Bench-V2 (Backend, Frontend, and Repo Exploration), proving that the introduction of visual capabilities does not degrade text-based reasoning.
Context
Z.ai's GLM-5V-Turbo lets a coding workflow use a screenshot or design mockup as input. The developer describes a model that takes a mockup or reference image and generates a runnable frontend project; it also accepts screenshots of faulty pages to help identify rendering problems and propose fixes. The usage documentation makes the input-output relationship explicit: visual material enters the model, while code and other text come out. This allows a developer to show the interface they want to build or repair without first translating every visible detail into a written description.
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