> For the complete documentation index, see [llms.txt](https://docs.ionos.com/cloud/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.ionos.com/cloud/ai/ai-model-hub/models/embedding-models/qwen3-vl-embedding-8b.md).
# Qwen3 VL Embedding 8B
**Summary:** Qwen3 VL Embedding 8B is a multimodal embedding model by Alibaba's Qwen team that generates semantic vector representations from both text and images. Supporting over 30 languages and a 32,768-token context window, this model excels in multimodal search, visual document retrieval, and cross-modal semantic matching, making it ideal for applications that require understanding across both textual and visual content such as image-text retrieval, screenshot search, and PDF document discovery.
| **Intelligence** | **Speed** | **Input** | **Output** |
| :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
|    |   |    |    |
| *High* | *Medium* | *Text, Image* | *Number Vector* |
## Central parameters
**Description:** Multimodal embedding model by Alibaba's Qwen team, generating 4096-dimensional vectors from text and image inputs across 30+ languages.
**Model identifier:** `Qwen/Qwen3-VL-Embedding-8B`
## IONOS CLOUD AI Model Hub Lifecycle and Alternatives
| **IONOS CLOUD Launch** | **End of Life** | **Alternative** | **Successor** |
| :--------------------: | :-------------: | :-------------: | :-----------: |
| *May 12, 2026* | N/A | | |
## Origin
| **Provider** | **Country** | **License** | **Flavor** | **Release** |
| :------------------------------------------------------------------------------: | :---------: | :--------------------------------------------------------------------------------------------: | :--------: | :---------------: |
| [**Qwen (Alibaba)**](https://qwenlm.github.io/) | Community | [**Apache 2.0**](https://www.apache.org/licenses/LICENSE-2.0) | - | *January 8, 2026* |
## Technology
| **Input Length** | **Parameters** | **Tensor Type** | **Multilingual** | **Further details** |
| :--------------: | :------------: | :-------------: | :--------------: | :----------------------------------------------------------------------------------------------------: |
| *32768* | *8B* | *bfloat16* | *Yes* | [**Hugging Face**](https://huggingface.co/Qwen/Qwen3-VL-Embedding-8B) |
**Input and output:** Each input produces one embedding vector, regardless of modality. A document can be text-only, image-only, or a combination of text and image, each produces a single vector up to 4096 dimensions.
## Modalities
| **Text** | **Image** | **Audio** |
| :--------------: | :-------: | :-----------: |
| Input and output | Input | Not supported |
## Endpoints
| **Chat Completions** | **Embeddings** | **Image generation** |
| :------------------: | :------------: | :------------------: |
| Not supported | v1/embeddings | Not supported |
## Features
| **Streaming** | **Reasoning** | **Tool calling** |
| :-----------: | :-----------: | :--------------: |
| Not supported | Not supported | Not supported |
## Usage examples
### Text embeddings
The following example demonstrates how to generate text embeddings using **Qwen3 VL Embedding 8B**.
**API Endpoint:** `POST https://openai.inference.de-txl.ionos.com/v1/embeddings`
**Request:**
```json
{
"model": "Qwen/Qwen3-VL-Embedding-8B",
"input": "The food was delicious and the waiter was friendly."
}
```
**Response:**
```json
{
"object": "list",
"data": [
{
"object": "embedding",
"embedding": [
0.0023064255,
-0.009327292,
0.0028842222
],
"index": 0
}
],
"model": "Qwen/Qwen3-VL-Embedding-8B",
"usage": {
"prompt_tokens": 10,
"total_tokens": 10
}
}
```
### Multimodal embeddings
The following example demonstrates how to generate embeddings from combined text and image input using **Qwen3 VL Embedding 8B**.
**Request:**
```json
{
"model": "Qwen/Qwen3-VL-Embedding-8B",
"messages": [
{
"role": "user",
"content": [
{
"type": "image_url",
"image_url": {
"url": "https://example.com/image.jpg"
}
},
{
"type": "text",
"text": "A product image showing a laptop"
}
]
}
],
"encoding_format": "float"
}
```
**Response:**
```json
{
"object": "list",
"data": [
{
"object": "embedding",
"embedding": [
0.0023064255,
-0.009327292,
0.0028842222
],
"index": 0
}
],
"model": "Qwen/Qwen3-VL-Embedding-8B",
"usage": {
"prompt_tokens": 261,
"total_tokens": 261
}
}
```
## Rate limits
Rate limits ensure fair usage and reliable access to the AI Model Hub. The [default rate limits](/cloud/ai/ai-model-hub/how-tos/rate-limits.md) apply to this model, separately from other models.
---
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