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Overview

GLM-4.5V is Z.AI’s new generation of visual reasoning models based on the MOE architecture. With a total of 106B parameters and 12B activation parameters, it achieves SOTA performance among open-source VLMs of the same level in various benchmark tests, covering common tasks such as image, video, document understanding, and GUI tasks.

Price

  • Input: $0.6 per million tokens
  • Output: $1.8 per million tokens

Input Modality

Video / Image / Text / File

Output Modality

Text

Maximum Output Tokens

16K

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Usage

Analyze webpage screenshots or screen recording videos, understand layout and interaction logic, and generate complete and usable webpage code with one click.
Precisely identify and locate target objects, suitable for practical scenarios such as security checks, quality inspections, content reviews, and remote sensing monitoring.
Recognize and process screen images, support execution of commands like clicking and sliding, providing reliable support for intelligent agents to complete operational tasks.
Deeply analyze complex documents spanning dozens of pages, support summarization, translation, chart extraction, and can propose insights based on content.
Strong reasoning ability and rich world knowledge, capable of deducing background information of images without using search.
Able to parse long video content and accurately infer the time, characters, events, and logical relationships within the video.
Can solve complex text-image combined problems, suitable for K12 educational scenarios for problem-solving and explanation.

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Resources

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Introducting GLM-4.5V

1

Open-Source Multimodal SOTA

GLM-4.5V, based on Z.AI’s flagship GLM-4.5-Air, continues the iterative upgrade of the GLM-4.1V-Thinking technology route, achieving comprehensive performance at the same level as open-source SOTA models in 42 public visual multimodal benchmarks, covering common tasks such as image, video, document understanding, and GUI tasks.Description
2

Support Thinking and Non-Thinking

GLM-4.5V introduces a new “Thinking Mode” switch, allowing users to freely switch between quick response and deep reasoning, flexibly balancing processing speed and output quality according to task requirements.

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Examples

  • Web Page Coding
  • GUI Agent
  • Chart Conversion
  • Grounding

Prompt

DescriptionPlease generate a high - quality UI interface using CSS and HTML based on the webpage I provided.

Display

Screenshot of the rendered web page:Description

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Quick Start

  • cURL
  • Python
  • Java
Basic Call
curl --location 'https://api.z.ai/api/paas/v4/chat/completions' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'Accept-Language: en-US,en' \
--header 'Content-Type: application/json' \
--data '{
"model": "glm-4.5v",
"messages": [
    {
        "role": "user",
        "content": [
            {
                "type": "image_url",
                "image_url": {
                    "url": "https://cloudcovert-1305175928.cos.ap-guangzhou.myqcloud.com/%E5%9B%BE%E7%89%87grounding.PNG"
                }
            },
            {
                "type": "text",
                "text": "Where is the second bottle of beer from the right on the table?  Provide coordinates in [[xmin,ymin,xmax,ymax]] format"
            }
        ]
    }
],
"thinking": {
    "type":"enabled"
}
}'
Streaming Call
curl --location 'https://api.z.ai/api/paas/v4/chat/completions' \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'Accept-Language: en-US,en' \
--header 'Content-Type: application/json' \
--data '{
"model": "glm-4.5v",
"messages": [
    {
        "role": "user",
        "content": [
            {
                "type": "image_url",
                "image_url": {
                    "url": "https://cloudcovert-1305175928.cos.ap-guangzhou.myqcloud.com/%E5%9B%BE%E7%89%87grounding.PNG"
                }
            },
            {
                "type": "text",
                "text": "Where is the second bottle of beer from the right on the table?  Provide coordinates in [[xmin,ymin,xmax,ymax]] format"
            }
        ]
    }
],
"thinking": {
    "type":"enabled"
},
"stream": true
}'
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