> For the complete documentation index, see [llms.txt](https://docs.cherryai.com.cn/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.cherryai.com.cn/docs/en-us/pre-basic/providers/cherryai/free-glm46v.md).
# Zhipu GLM-4.6V
Cherry Studio users can now use the built-in **CherryIN** free trial of the service **Zhipu GLM-4.6V**β a vision flagship model released by Z.ai (Zhipu AI) in December 2025, with a MoE architecture, 128K native multimodal context, and native multimodal tool calling, making it the top choice for image-text understanding and multimodal Agent scenarios.
***
## π What is GLM-4.6V?
GLM-4.6V is the latest-generation vision-language model in Z.ai's GLM-V series, natively supporting unified text + image modeling and further expanding context and tool-calling capabilities on the basis of GLM-4.5V.
* Architecture: Mixture-of-Experts (MoE)
* Total parameters: 106B
* Active parameters: about 12B
* Context length: 128K tokens
* Open-source license: MIT
* Release date: December 8β9, 2025
* Visual encoder: supports multi-resolution images (up to 4K)
The series also includes **GLM-4.6V-Flash (9B)**, designed for local and low-latency scenarios, free for commercial use.
***
## π Continuing the multimodal training system of the GLM-V series
GLM-4.6V follows the technical approach of GLM-4.1V-Thinking / GLM-4.5V and further strengthens vision and Agent capabilities:
1. **Native multimodal modeling**: joint training of text and images, supporting mixed text-image input
2. **Context expansion**: training context extended to 128K tokens, able to process about 150 pages of dense documents, 200 pages of slides, or 1 hour of video in a single pass
3. **Native multimodal tool calling**: tools can directly receive and return images, processing multimodal artifacts via URL based on the extended MCP protocol
4. **Reinforcement learning enhancement**: continues the scalable RL process of the GLM-V series
***
## βοΈ Native multimodal, designed for real-world scenarios
GLM-4.6V's multimodal capabilities cover everyday and professional scenarios:
* β **Rich text content understanding**: long documents, multi-page text, and mixed text-image layouts
* β **Visual web search**: online retrieval and understanding combined with visual input
* β **Frontend recreation**: generate frontend code from design drafts or UI screenshots
* β **Long-context multimodal document analysis**: whole PDF / slides / video-level input
* β **Chart and table parsing**: structured information extraction
***
## π‘ Native multimodal tool calling and Agent capabilities
One of the core upgrades of GLM-4.6V is **"visual perception β executable action"** the closed loop: tool calling natively supports images as both input and output, enabling multimodal Agents to be deployed in real business scenarios.
| Scenario | Recommended usage | Example |
| ------------------------ | -------------------- | --------------------------------------------------------- |
| Simple image-text Q\&A | Direct conversation | "Whatβs in this picture?" |
| Moderately complex tasks | Enable tool calling | Retrieve data after reading charts |
| Complex multimodal Agent | Multiple tools + MCP | Screenshot β understanding β API call β report generation |
***
## π Efficient MoE, open and available
* β‘ MoE sparse activation: 106B total parameters, only about 12B activated
* π° Through CherryIN in Cherry Studio**free to use**
* π₯οΈ Weights, inference code, and MCP tools are open-sourced on GitHub and Hugging Face, under the MIT license
***
## π§ Focused on practical capabilities: multimodal assistant
GLM-4.6V is suitable for the following scenarios in actual use:
* **Document assistant**: read and summarize full-length documents, scans, and slides
* **Data analysis**: identify and interpret charts and dashboard screenshots
* **Frontend and design**: generate or modify frontend code based on UI screenshots
* **Visual search**: combine images for online retrieval and information integration
* **Multimodal Agent**: complete complex tasks with tools such as browser, code execution, and retrieval
***
## π§ How to use it in Cherry Studio?
1. Open Cherry Studio and go to **Settings β Model Services**.
2. find **CherryIN** the service provider and enable it.
3. In the model list, select **Zhipu GLM-4.6V**.
4. Return to the chat screen and switch to **GLM-4.6V**, you can directly upload images in the conversation for image-text interaction.
> π‘ Tip: The free model quota provided by CherryIN is borne by the official Cherry Studio, suitable for daily experience and evaluation; for production environments, it is recommended to use the official Z.ai (Zhipu) API.
***
π **Experience Zhipu GLM-4.6V now and unlock native multimodal and visual Agent capabilities!**
***
### π‘ Get help and submit feedback
If you encounter any questions, bugs, or have suggestions for feature improvements during configuration or use, please refer to [Feedback and Suggestions](/docs/en-us/question-contact/suggestions.md) the official channels provided there.
---
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