GLM-5V-Turbo - A native multimodal coding foundation model launched by Zhipu AI

What is GLM-5V-Turbo?

GLM-5V-Turbo is a native multimodal coding foundation model launched by Zhipu AI, designed specifically for visual programming and AI agents. The model deeply integrates visual and text capabilities from the pre-training stage, supporting the understanding of multimodal inputs such as images, videos, and design drafts, with a context window of up to 200k. The model can understand screenshots and generate complete, runnable code, achieving leading performance in benchmark tests such as Design2Code and GUI Agent. It also collaborates deeply with agents such as Claude Code and AutoClaw, providing "image-based code writing" and autonomous task execution capabilities, realizing a paradigm shift from pure text to visual interaction in programming.

Main functions of GLM-5V-Turbo

• Design draft to codeIt automatically generates complete and runnable front-end project code based on sketches, UI design drafts, or website screenshots, accurately reproducing the layout, color scheme, and interaction logic.
• GUI self-replicatingThe model can autonomously browse the target website and collect page structure, navigation relationships and visual materials, and finally generate code to replicate the entire website.
• Interactive Iterative EditingIt supports visual iteration of the generated code, allowing users to add or remove page modules, adjust style layouts, and add interactive features such as button feedback and form linkage as needed.
• Multimodal native understandingIt natively supports understanding multimodal input such as images, videos, design drafts, and document layouts, and integrates the ability to call tools such as drawing frames, screenshots, and web page reading, with a context window size of up to 200k.
• Agent Visual EnhancementIt deeply adapts to frameworks such as Claude Code and AutoClaw, realizing a complete closed loop of "understanding the environment → planning actions → executing tasks", giving the Agent true visual perception capabilities.
• GUI autonomous controlIt has the ability to operate autonomously in real graphical interface environments such as Android and Web, and can complete element positioning, page navigation and task execution.
• Financial Chart AnalysisThe model can directly understand K-line trends, valuation range charts, and complex charts in brokerage research reports, and automatically generate professional analysis reports or PPTs with rich graphics and text.
• Multimodal in-depth researchIt supports multimodal search and parallel data acquisition, and can integrate multiple information sources to complete in-depth research and output structured content.
• Skills available right out of the boxIt provides an official skill library, integrating functions such as OCR text recognition, table recognition, handwriting recognition, formula recognition, text-to-image conversion, and resume screening. It can be installed and used with one click.

How to use GLM-5V-Turbo

• Direct product experience
  • AutoClaw (澳龙)Visit the AutoClaw website to experience Agent visual capabilities and skills such as "stock analyst".
  • Z.aiVisit the Z.ai website to directly engage in multimodal dialogue and programming tasks.
• API Development and Integration
  • BigModel Open PlatformObtain the API documentation and interface from https://docs.bigmodel.cn/cn/guide/models/vlm/glm-5v-turbo.
  • Z.ai Developer PlatformVisit https://docs.z.ai/guides/vlm/glm-5v-turbo for the access guide.
• Coding Plan Application (Priority Trial)
  • Applications are now open to Coding Plan users and will be formally incorporated into the GLM Coding Plan in the future.
  • Application method: Fill out the Feishu questionnaire https://zhipu-ai.feishu.cn/share/base/form/shrcndgpmRlJoD5rMmIavUrPwzg.

Key information and usage requirements for GLM-5V-Turbo

• Model localizationA native multimodal coding foundation model designed for visual programming and AI agent scenarios.
• Context windowSupports 200k tokens.
• Core ArchitectureIt adopts the new generation CogViT visual encoder, combined with the MTP structure that is compatible with multimodal input and inference-friendly.
• Performance benchmarkThe scores are 94.8 on Design2Code, 75.7 on AndroidWorld, and 88.5 on WebVoyager, maintaining the same level of performance as visual programming on the CC-Bench-V2 plain text programming benchmark.
• Training methods30+ task-based collaborative reinforcement learning, covering sub-domains such as STEM, grounding, video, and GUI Agent, ensuring that multiple capabilities are enhanced collaboratively rather than degraded.
• toolchainIt natively supports multimodal tools such as drawing frames, taking screenshots, reading web pages, and multimodal search.
• Ecological integrationDeeply compatible with Agent frameworks such as Claude Code and AutoClaw, providing an official Skills library that is ready to use out of the box.

GLM-5V-Turbo's core advantages

• Native multimodal deep fusionThe technology integrates visual and textual capabilities natively from the pre-training stage, rather than splicing them together later, to truly enable users to "understand the images and write code".
• Leading in visual programming capabilitiesIt outperforms similar models in core benchmark tests such as Design2Code (94.8 points) and Flame-VLM-Code (93.8 points), and supports accurate reproduction from sketches to complete front-end projects.
• Plain text capability with zero degradationThrough multi-task collaborative reinforcement learning technology, it ensures that visual capabilities are enhanced while plain text programming, reasoning, and tool calling capabilities remain at the original level, and performs stably in the CC-Bench-V2 test.
• Agent visual perception enhancementIt is deeply adapted to Agent frameworks such as Claude Code and AutoClaw, giving it the ability to "understand the screen" and performs outstandingly on GUI control benchmarks such as AndroidWorld (75.7 points) and WebVoyager (88.5 points).
• Complete multimodal toolchainIt natively supports tools such as drawing frames, taking screenshots, reading web pages, and multimodal search, extending the perception-action link of programming and task execution from plain text to visual interaction.
• 30+ Task Collaboration OptimizationBy using collaborative reinforcement learning covering fields such as STEM, grounding, video, and GUI Agents, we can achieve a balanced improvement in capabilities such as perception, reasoning, and agentic execution, avoiding the neglect of capabilities caused by single-domain training.

Comparison of GLM-5V-Turbo with similar competing products

Application scenarios of GLM-5V-Turbo

• Front-end intelligent developmentIt can automatically generate a complete front-end project based on sketches, UI design drafts, or website screenshots, and supports website cloning and interactive function iteration.
• Agent Visual EnhancementIt provides visual perception capabilities to frameworks such as Claude Code and AutoClaw, enabling them to browse web pages, interact with interfaces, and perform complex tasks.
• Financial data analysisIt directly interprets candlestick charts, valuation range charts, and brokerage research report charts, and collects data from multiple sources in parallel to generate professional analysis reports or PPTs with rich graphics and text.
• Multimodal in-depth researchIt supports in-depth information retrieval and question answering by combining images, videos, and documents, and realizes functions such as visual grounding, image captioning, and OCR recognition.
• Enterprise Automated WorkflowThe model can directly understand design drafts for D2C development, process business documents containing complex charts, and complete automated testing and interface verification based on visual information.