# LLM

All AI large language models used in GM products are listed below. We hope this information is helpful to you. We are continuously following up on and evaluating more large language models, and will integrate them in a timely manner based on product needs to provide users with a richer experience.

## GPT-4o-mini <a href="#gpt-4o-mini" id="gpt-4o-mini"></a>

<figure><img src="/files/gWwXS7cEBjEQV2HRUi9n" alt=""><figcaption></figcaption></figure>

**See more details**

{% embed url="<https://platform.openai.com/docs/overview>" %}

***

## Gemini 2.0 Flash-Lite <a href="#gemini-2.0-flash-lite" id="gemini-2.0-flash-lite"></a>

<figure><img src="/files/O8sifo1dxG4CGFaHWCJK" alt=""><figcaption></figcaption></figure>

**See more detail**

{% embed url="<https://ai.google.dev/gemini-api/docs>" %}

***

## Claude 3.5 Haiku <a href="#claude-3.5-haiku" id="claude-3.5-haiku"></a>

<figure><img src="/files/dwl3NyihUsTSvsXoT0rR" alt=""><figcaption></figcaption></figure>

**See more details**

{% embed url="<https://docs.anthropic.com/en/home>" %}


---

# 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://gm-sporting.gitbook.io/docs/app/llm.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.