> 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/bge-m3.md).
# BGE M3
**Summary:** BGE M3 is a versatile multilingual embedding model that supports over 100 languages with an extended 8192 token context window, offering both dense and sparse retrieval capabilities. This model excels in cross-language information retrieval, multilingual document analysis, and global content discovery, making it essential for international applications, multilingual search systems, and global knowledge management platforms where language diversity, long-context understanding, and scalability are critical.
| **Intelligence** | **Speed** | **Input** | **Output** |
| :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |
|    |   |    |    |
| *High* | *Medium* | *Text* | *Number Vector* |
## Central parameters
**Description:** Multilingual embedding model by Beijing Academy of Artificial Intelligence with extended input length support and 1024-dimensional output vectors.
**Model identifier:** `BAAI/bge-m3`
## IONOS CLOUD AI Model Hub Lifecycle and Alternatives
| **IONOS CLOUD start date** | **End of Life** | **Alternative** | **Successor** |
| :------------------------: | :-------------: | :--------------------------------------------------------------------------------------------------------------------: | :-----------: |
| *January 1, 2025* | N/A | [**BGE Large V1.5**](/cloud/ai/ai-model-hub/models/embedding-models/bge-large-1-5.md) | |
## Origin
| **Provider** | **Country** | **License** | **Flavor** | **Release** |
| :---------------------------------------------------------------------: | :---------: | :-----------------------------------------------------------------------------------------------------------: | :--------: | :----------------: |
| [**BAAI**](https://www.baai.ac.cn/en/) | Community | [**License**](https://github.com/FlagOpen/FlagEmbedding/blob/master/LICENSE) | - | *January 28, 2024* |
## Technology
| **Input Length** | **Parameters** | **Tensor Type** | **Multilingual** | **Further details** |
| :--------------: | :------------: | :-------------: | :--------------: | :-------------------------------------------------------------------------------------: |
| *8192* | *568M* | *float* | *Yes* | [**Hugging Face**](https://huggingface.co/BAAI/bge-m3) |
## Modalities
| **Text** | **Image** | **Audio** |
| :--------------: | :-----------: | :-----------: |
| Input and output | Not supported | 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 example
### Embedding example
The following example demonstrates how to generate text embeddings using **BGE M3**.
**API Endpoint:** `POST https://openai.inference.de-txl.ionos.com/v1/embeddings`
**Request:**
```json
{
"model": "BAAI/bge-m3",
"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": "BAAI/bge-m3",
"usage": {
"prompt_tokens": 10,
"total_tokens": 10
}
}
```
## 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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