# Zhipu GLM-4.6V

Cherry Studio users can now, through the built-in **CherryIN** service, experience it for free **Zhipu GLM-4.6V**— a flagship vision model released by Z.ai (Zhipu AI) in December 2025, featuring a MoE architecture, 128K native multimodal context, and native multimodal tool calling. It is the preferred choice for image-text understanding and multimodal Agent scenarios.

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## 🚀 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 extending context and tool-calling capabilities based on GLM-4.5V.

* Architecture: Mixture-of-Experts (MoE)
* Total parameters: 106B
* Activated parameters: about 12B
* Context length: 128K tokens
* Open-source license: MIT
* Release date: December 8–9, 2025
* Vision 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.

<figure><img src="/files/4443a1d3ef592dd1d2eb3e722a2b4484c7a3e1c4" alt=""><figcaption></figcaption></figure>

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## 📚 Continuing the multimodal training system of the GLM-V series

GLM-4.6V follows the technical path of GLM-4.1V-Thinking / GLM-4.5V and has been further enhanced in vision and Agent capabilities:

1. **Native multimodal modeling**: joint training of text and images, supporting mixed text-image input
2. **Context expansion**: training context expanded to 128K tokens, able to process about 150 pages of dense documents, 200 pages of slides, or 1 hour of video in a single run
3. **Native multimodal tool calling**: tools can directly receive and return images, handling multimodal outputs via URL based on the extended MCP protocol
4. **Reinforcement learning enhancements**: continues the scalable RL pipeline of the GLM-V series

<figure><img src="/files/a65c7b6797bb19f1558abd5e684c889250f9475e" alt=""><figcaption></figcaption></figure>

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## ⚙️ Native multimodal, built for real-world scenarios

GLM-4.6V's multimodal capabilities cover both everyday and professional scenarios:

* ✅ **Rich-text content understanding**: long documents, multi-page text, and mixed text-image layouts
* ✅ **Visual web search**: web search and understanding combined with visual input
* ✅ **Frontend recreation**: generate frontend code from design mockups or UI screenshots
* ✅ **Long-context multimodal document analysis**: full PDF / slide deck / video-level input
* ✅ **Chart and table parsing**: structured information extraction

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## 💡 Native multimodal tool calling and Agent capabilities

One of GLM-4.6V's core upgrades is the **"visual perception → executable action"** 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  | "What is in this image?"                             |
| Moderately complex tasks | Enable tool calling  | Read the chart and then retrieve the data            |
| Complex multimodal Agent | Multiple tools + MCP | Screenshot → understand → call API → generate report |

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## 🌟 Efficient MoE, openly available

* ⚡ MoE sparse activation: 106B total parameters, only about 12B activated
* 💰 Through CherryIN in Cherry Studio**free to use**
* 🖥️ The weights, inference code, and MCP tools have been open-sourced on GitHub and Hugging Face under the MIT license

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## 🧠 Focus on practical capabilities: multimodal assistant

In actual use, GLM-4.6V is suitable for the following scenarios:

* **Document assistant**: read and summarize long documents, scans, and slide decks
* **Data analysis**: identify and interpret charts and dashboard screenshots
* **Frontend and design**: generate or modify frontend code based on UI screenshots
* **Visual search**: web search and information integration combined with images
* **Multimodal Agent**: complete complex tasks using tools such as browsers, code execution, and retrieval

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## 🧭 How to use it in Cherry Studio?

1. Open Cherry Studio and go to **Settings → 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 interface and switch the top model selector to **GLM-4.6V**, then you can upload images directly in the conversation for image-text interaction.

> 💡 Tip: The free model quota provided by CherryIN is covered by the Cherry Studio official team, making it suitable for everyday trials and evaluations; for production environments, it is recommended to use the official Z.ai (Zhipu) API.

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📘 **Try Zhipu GLM-4.6V now and unlock native multimodal and visual Agent capabilities!**


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