# 嵌入模型

{% hint style="info" %}
为了防止出错，在本文档中部分模型的 max input 的值没有写成极限值，如：在官方给出的最大输入值为8k（未明确给出具体数值）时，本文档中给出的参考值为8191或8000等。（看不懂忽视，按照文档中的参考值填写即可）
{% endhint %}

### 火山-豆包

[官方模型信息参考地址](https://console.volcengine.com/ark/region:ark+cn-beijing/model?feature=\&projectName=default\&vendor=Bytedance\&view=LIST_VIEW)

| 名称                      | max input |
| ----------------------- | --------- |
| Doubao-embedding        | 4095      |
| Doubao-embedding-vision | 8191      |
| Doubao-embedding-large  | 4095      |

### 阿里

[官方模型信息参考地址](https://help.aliyun.com/zh/model-studio/user-guide/embedding?spm=a2c4g.11186623.0.i1)

| 名称                      | max input |
| ----------------------- | --------- |
| text-embedding-v3       | 8192      |
| text-embedding-v2       | 2048      |
| text-embedding-v1       | 2048      |
| text-embedding-async-v2 | 2048      |
| text-embedding-async-v1 | 2048      |

### OpenAI

[官方模型信息参考地址](https://platform.openai.com/docs/guides/embeddings#embedding-models)

| 名称                     | max input |
| ---------------------- | --------- |
| text-embedding-3-small | 8191      |
| text-embedding-3-large | 8191      |
| text-embedding-ada-002 | 8191      |

### 百度

[官方模型信息参考地址](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/om6070n97#%E8%AF%B7%E6%B1%82%E5%8F%82%E6%95%B0)

| 名称           | max input |
| ------------ | --------- |
| Embedding-V1 | 384       |
| tao-8k       | 8192      |

### 智谱

[官方模型信息参考地址](https://bigmodel.cn/console/modelcenter/square)

| 名称          | max input |
| ----------- | --------- |
| embedding-2 | 1024      |
| embedding-3 | 2048      |

### 混元

[官方模型信息参考地址](https://cloud.tencent.com/document/product/1729/102832)

| 名称                | max input |
| ----------------- | --------- |
| hunyuan-embedding | 1024      |

### 百川

[官方模型信息参考地址](https://platform.baichuan-ai.com/docs/text-Embedding)

| 名称                      | max input |
| ----------------------- | --------- |
| Baichuan-Text-Embedding | 512       |

### together

[官方模型信息参考地址](https://docs.together.ai/docs/serverless-models#embedding-models)

| 名称                        | max input |
| ------------------------- | --------- |
| M2-BERT-80M-2K-Retrieval  | 2048      |
| M2-BERT-80M-8K-Retrieval  | 8192      |
| M2-BERT-80M-32K-Retrieval | 32768     |
| UAE-Large-v1              | 512       |
| BGE-Large-EN-v1.5         | 512       |
| BGE-Base-EN-v1.5          | 512       |

### Jina

[官方模型信息参考地址](https://jina.ai/models/jina-embedding-b-en-v1)

| 名称                                 | max input |
| ---------------------------------- | --------- |
| jina-embedding-b-en-v1             | 512       |
| jina-embeddings-v2-base-en         | 8191      |
| jina-embeddings-v2-base-zh         | 8191      |
| jina-embeddings-v2-base-de         | 8191      |
| jina-embeddings-v2-base-code       | 8191      |
| jina-embeddings-v2-base-es         | 8191      |
| jina-colbert-v1-en                 | 8191      |
| jina-reranker-v1-base-en           | 8191      |
| jina-reranker-v1-turbo-en          | 8191      |
| jina-reranker-v1-tiny-en           | 8191      |
| jina-clip-v1                       | 8191      |
| jina-reranker-v2-base-multilingual | 8191      |
| reader-lm-1.5b                     | 256000    |
| reader-lm-0.5b                     | 256000    |
| jina-colbert-v2                    | 8191      |
| jina-embeddings-v3                 | 8191      |

### 硅基流动

[官方模型信息参考地址](https://siliconflow.cn/zh-cn/models)

| 名称                                    | max input |
| ------------------------------------- | --------- |
| BAAI/bge-m3                           | 8191      |
| netease-youdao/bce-embedding-base\_v1 | 512       |
| BAAI/bge-large-zh-v1.5                | 512       |
| BAAI/bge-large-en-v1.5                | 512       |
| Pro/BAAI/bge-m3                       | 8191      |

### Gemini

[官方模型信息参考地址](https://ai.google.dev/gemini-api/docs/models/gemini?hl=zh-cn#text-embedding)

| 名称                 | max input |
| ------------------ | --------- |
| text-embedding-004 | 2048      |

### nomic

[官方模型信息参考地址](https://docs.nomic.ai/atlas/embeddings-and-retrieval/text-embedding)

| 名称                    | max input |
| --------------------- | --------- |
| nomic-embed-text-v1   | 8192      |
| nomic-embed-text-v1.5 | 8192      |
| gte-multilingual-base | 8192      |

### console

[官方模型信息参考地址](https://console.upstage.ai/docs/capabilities/embeddings)

| 名称                | max input |
| ----------------- | --------- |
| embedding-query   | 4000      |
| embedding-passage | 4000      |

### cohere

[官方模型信息参考地址](https://docs.cohere.com/docs/models#embed)

| 名称                            | max input |
| ----------------------------- | --------- |
| embed-english-v3.0            | 512       |
| embed-english-light-v3.0      | 512       |
| embed-multilingual-v3.0       | 512       |
| embed-multilingual-light-v3.0 | 512       |
| embed-english-v2.0            | 512       |
| embed-english-light-v2.0      | 512       |
| embed-multilingual-v2.0       | 256       |


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.cherry-ai.com/knowledge-base/emb-models-info.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.