> ## Documentation Index
> Fetch the complete documentation index at: https://docs.gmicloud.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Kimi K2.5

> Kimi K2.5 is an open-source, native multimodal agentic model built through continual pretraining on approximately 15 trillion mixed visual and text tokens atop Kimi-K2-Base.

**Model ID**

```bash theme={null}
moonshotai/Kimi-K2.5
```

## API Usage

You can interact with the Moonshotai Kimi K2 Instruct 0905 model through various programming languages and methods. Below are examples showing how to use the model's API.

## API Examples

Generate a model response using the chat endpoint of Moonshotai Kimi K2 Instruct 0905.

### Shell

```bash theme={null}
curl --request POST \
  --url https://api.gmi-serving.com/v1/chat/completions \
  -H 'Content-Type: application/json' \
  -H 'Authorization: Bearer *************' \
  --data '{
    "model": "moonshotai/Kimi-K2.5",
    "messages": [
      {"role": "system", "content": "You are a helpful AI assistant"},
      {"role": "user", "content": "List 3 countries and their capitals."}
    ],
    "temperature": 0,
    "max_tokens": 500
  }'
```

### Python

```python theme={null}
import requests
import json

url = "https://api.gmi-serving.com/v1/chat/completions"
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer *************"
}

payload = {
    "model": "moonshotai/Kimi-K2.5",
    "messages": [
        {"role": "system", "content": "You are a helpful AI assistant"},
        {"role": "user", "content": "List 3 countries and their capitals."}
    ],
    "temperature": 0,
    "max_tokens": 500
}

response = requests.post(url, headers=headers, json=payload)
print(json.dumps(response.json(), indent=2))
```