> For the complete documentation index, see [llms.txt](https://docs.uomi.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.uomi.ai/build/build-an-agent/available-ai-models.md).

# Available AI Models

## Available AI Models

### Overview

[WASP](https://github.com/Uomi-network/WASP) provides access to cutting-edge AI models through a simple and efficient interface. Each model is carefully selected to offer high-performance.

### Current Model Lineup

|  ID |   Name  |                Model                |      Type      | Parameters |
| :-: | :-----: | :---------------------------------: | :------------: | :--------: |
|  1  | Qwen2.5 | Qwen/Qwen2.5-32B-Instruct-GPTQ-Int4 | Language Model | 32 Billion |

### Detailed Model Insights

#### Qwen2.5-32B-Instruct

The Qwen2.5 model represents the latest advancement in large language model technology. Developed by Alibaba's Qwen team, this model brings several key innovations:

* **High-Performance Instruction Following**: Specifically designed to understand and execute complex instructions with remarkable accuracy.
* **Efficient Quantization**: Utilizing GPTQ (Generative Pretrained Transformer Quantization) with INT4 precision, the model maintains high performance while reducing computational requirements.
* **Broad Capability Range**: Excels in tasks such as:
  * Natural language understanding
  * Text generation
  * Contextual reasoning
  * Multilingual communication

**Technical Specifications**:

* Model Size: 32 Billion parameters
* Quantization: INT4
* Optimization: GPTQ
* Primary Use: Instruction-based AI interactions

### More models coming soon...

***

**Last Updated**: February 2025


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## 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, and the optional `goal` query parameter:

```
GET https://docs.uomi.ai/build/build-an-agent/available-ai-models.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

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.
