# GLM 4.5V

Vision-language capability built on GLM-4.5-Air, covering image reasoning, video understanding, GUI tasks, and visual grounding.

- **Model ID:** `zai/glm-4.5v`
- **Type:** chat
- **Providers:** novita, zai
- **Context window:** 66,000
- **Maximum output tokens:** 16,384
- **Pricing:** $0.6/1M input tokens, $1.8/1M output tokens
- **Canonical page:** https://vercel.com/ai-gateway/models/glm-4.5v

## Supported parameters

Detailed capability metadata has not been reported for this model.

## Example

```ts
import { streamText } from 'ai'

const result = streamText({
  model: 'zai/glm-4.5v',
  prompt: 'Why is the sky blue?'
})
```

## About

GLM 4.5V extends the GLM-4.5-Air foundation with multimodal vision capabilities. Built by Z.AI, it targets image reasoning, document understanding, and visual grounding tasks at a comparable scale to other models in its class.

The model supports a broad range of visual input types: single images, multi-image analysis, long video understanding with event recognition, complex chart and document parsing, and GUI task handling including screen reading and icon recognition. A distinctive feature is visual grounding, where the model localizes specific elements in images with bounding box coordinates, enabling applications that need to point at or interact with visual content programmatically.

GLM 4.5V includes a thinking mode switch that balances quick responses against deeper reasoning. For straightforward visual questions, disable thinking for fast responses. For complex multi-image analysis or document interpretation, enable thinking to improve accuracy. The model operates within a context window of 66K tokens.

## What to consider

High-resolution images consume more input tokens. Consider resizing images to the minimum resolution your task requires to control costs.

Enable thinking for complex visual reasoning tasks (chart analysis, multi-image comparison). Disable it for simple captioning or classification to reduce latency.

When using visual grounding, the model returns bounding box coordinates normalized by image dimensions. Your application needs to handle this coordinate format for downstream processing.

## When to use

### Best For

- **Document and chart understanding** where parsing complex layouts with mixed text, tables, and figures requires joint visual-textual reasoning
- **GUI automation and testing** leveraging screen reading, icon recognition, and visual element localization
- **Multi-image analysis** comparing multiple images or analyzing image sequences in a single request
- **Long video understanding** with event recognition and temporal reasoning across extended video content
- **Visual grounding tasks** where you need precise bounding box coordinates for detected elements

### Consider Alternatives When

- You need text-only capabilities without vision input. GLM-4.5 or GLM-4.5-Air provides the same language foundation without the vision overhead
- Your task requires image generation or visual output. GLM 4.5V is input-multimodal only and produces text output
- You need vision features beyond GLM-4.5V. GLM-4.6V offers an upgraded 128K context window and native multimodal function calling
- Pixel-accurate frontend replication from screenshots is required. GLM-4.6V includes targeted improvements for HTML/CSS reconstruction

## Best for

- **Document and chart understanding:** Parsing complex layouts with mixed text, tables, and figures requires joint visual-textual reasoning
- **GUI automation and testing:** Screen reading, icon recognition, and visual element localization in one model
- **Multi-image analysis:** Multiple images or image sequences processed in a single request
- **Long video understanding:** Event recognition and temporal reasoning across extended video content
- **Visual grounding tasks:** Bounding box coordinates for detected elements are returned natively

## Consider alternatives

- **Text-only capabilities:** GLM-4.5 or GLM-4.5-Air provides the same language foundation without the vision overhead
- **Image generation needed:** GLM 4.5V is input-multimodal only and produces text output
- **Advanced vision features:** GLM-4.6V offers an upgraded 128K context window and native multimodal function calling
- **Pixel-accurate frontend replication:** GLM-4.6V includes targeted improvements for HTML/CSS reconstruction from screenshots

## Frequently asked questions

### What visual inputs does GLM 4.5V support?

Single images, multiple images, long videos, screenshots, charts, documents, and GUI interfaces. It processes these alongside text prompts in a single request.

### What is visual grounding in GLM 4.5V?

Visual grounding lets the model identify and localize specific elements in images by returning bounding box coordinates. Coordinates are normalized by image dimensions, enabling programmatic interaction with detected visual elements.

### Does GLM 4.5V support video input?

Yes. It handles long video understanding with event recognition and temporal reasoning, processing extended video content within the context window.

### How does the thinking mode work?

You can toggle thinking on or off per request. Thinking mode enables deeper chain-of-thought reasoning for complex visual tasks. Disabling it provides faster, more direct responses for simpler queries.

### How do I authenticate with GLM 4.5V through AI Gateway?

AI Gateway provides a unified API key. No separate Z.AI account is needed. Configure your API key and use the model identifier to route requests. BYOK is also supported for direct provider accounts.

### How does GLM 4.5V compare to GLM-4.6V?

GLM 4.5V builds on GLM-4.5-Air and targets vision-language tasks at its scale. GLM-4.6V is the next generation with a 128K context window, native multimodal function calling, and improved frontend replication capabilities.

### Can GLM 4.5V generate images?

No. GLM 4.5V accepts visual inputs and produces text output only. For image generation, use a dedicated image generation model.

## Links

- [Model page](https://vercel.com/ai-gateway/models/glm-4.5v)
- [AI Gateway documentation](https://vercel.com/docs/ai-gateway)
- [Provider model documentation](https://novita.ai/models)
- [Provider pricing](https://docs.z.ai/guides/overview/pricing)


If you encounter incorrect information, can’t find what you need, need a capability Vercel doesn’t currently offer, or have any other feedback to report, please do it by following the instructions at https://vercel.com/feedback.md.