# 雲端模型推論 API 服務

## 大型語言模型（LLM）

<table><thead><tr><th width="224.984375"></th><th>AWS Bedrock</th><th>Google Vertex AI</th><th>Azure AI</th></tr></thead><tbody><tr><td>Claude Model</td><td>✅️</td><td>✅️</td><td></td></tr><tr><td>GPT Model</td><td></td><td></td><td>✅️</td></tr><tr><td>Gemini Model</td><td></td><td>✅️</td><td></td></tr></tbody></table>

## 向量嵌入模型（Embedding Model）

<table><thead><tr><th width="225.39453125"></th><th>AWS Bedrock</th><th>Google Vertex AI</th><th>Azure AI</th></tr></thead><tbody><tr><td>Cohere Embedding</td><td>✅️</td><td></td><td>✅️</td></tr><tr><td>OpenAI Embedding</td><td></td><td></td><td>✅️</td></tr><tr><td>Gemini Embedding</td><td></td><td>✅️</td><td></td></tr></tbody></table>

## 重排序模型（Reranker Model）

<table><thead><tr><th width="225.01171875"></th><th>AWS Bedrock</th><th>Google Vertex AI</th><th>Azure AI</th></tr></thead><tbody><tr><td>Cohere Reranker</td><td>✅️</td><td></td><td>✅️</td></tr><tr><td>Gemini Reranker</td><td></td><td>✅️</td><td></td></tr></tbody></table>


---

# 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.maiagent.ai/tech/platform-development/cloud-model-inference-api-service.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.