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

# Models

Retrieve the list of models currently available on the DOS AI platform. This endpoint is useful for dynamically discovering which models you can use without hard-coding model IDs.

## Endpoint

```
GET https://api.dos.ai/v1/models
```

## Authentication

Include your API key in the `Authorization` header:

```
Authorization: Bearer dos_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
```

## Request

No request body or query parameters are required.

## Response

### Success (200 OK)

```json
{
  "object": "list",
  "data": [
    {
      "id": "dos-ai",
      "object": "model",
      "created": 1711000000,
      "owned_by": "dos-ai",
      "context_length": 131072,
      "pricing": {
        "prompt": "0.00000015",
        "completion": "0.00000015"
      }
    },
    {
      "id": "deepseek/deepseek-chat",
      "object": "model",
      "created": 1711000000,
      "owned_by": "deepseek",
      "context_length": 131072,
      "pricing": {
        "prompt": "0.00000014",
        "completion": "0.00000028"
      }
    },
    {
      "id": "qwen/qwen-2.5-72b-instruct",
      "object": "model",
      "created": 1711000000,
      "owned_by": "alibaba",
      "context_length": 131072,
      "pricing": {
        "prompt": "0.00000035",
        "completion": "0.00000035"
      }
    }
  ]
}
```

### Response Fields

| Field                       | Type    | Description                                                                 |
| --------------------------- | ------- | --------------------------------------------------------------------------- |
| `object`                    | string  | Always `"list"`.                                                            |
| `data`                      | array   | Array of model objects.                                                     |
| `data[].id`                 | string  | The model identifier. Use this as the `model` parameter in API requests.    |
| `data[].object`             | string  | Always `"model"`.                                                           |
| `data[].created`            | integer | Unix timestamp of when the model was added.                                 |
| `data[].owned_by`           | string  | The organization that owns or hosts the model.                              |
| `data[].context_length`     | integer | Maximum context window in tokens.                                           |
| `data[].pricing`            | object  | OpenRouter-compatible pricing metadata.                                     |
| `data[].pricing.prompt`     | string  | Price per input/prompt token in USD as a string (e.g. `"0.00000014"`).      |
| `data[].pricing.completion` | string  | Price per output/completion token in USD as a string (e.g. `"0.00000028"`). |

## Retrieve Model (`GET /v1/models/:model_id`)

Retrieve metadata and pricing for a single model:

```bash
curl https://api.dos.ai/v1/models/dos-ai
```

The `id` field is the value you use when specifying a model in API requests:

| Model Name      | Model ID        |
| --------------- | --------------- |
| Qwen3.5-35B-A3B | `dos-ai`        |
| Llama 3.3 70B   | `llama-3.3-70b` |
| DeepSeek V3     | `deepseek-v3`   |
| Llama 3.1 8B    | `llama-3.1-8b`  |

## Error Responses

| Status Code | Description                 |
| ----------- | --------------------------- |
| 401         | Invalid or missing API key. |
| 500         | Internal server error.      |

See [Error Codes](/support/error-codes.md) for details.

## Examples

### cURL

```bash
curl https://api.dos.ai/v1/models \
  -H "Authorization: Bearer dos_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
```

### Python

```python
from openai import OpenAI

client = OpenAI(
    api_key="dos_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
    base_url="https://api.dos.ai/v1"
)

models = client.models.list()
for model in models.data:
    print(model.id)
```

### Node.js

```javascript
import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "dos_sk_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
  baseURL: "https://api.dos.ai/v1",
});

const models = await client.models.list();
for (const model of models.data) {
  console.log(model.id);
}
```

> **Note:** The list of available models may change over time as new models are added. We recommend fetching the model list dynamically rather than hard-coding model IDs in your application.


---

# 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 by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.dos.ai/api-reference/models.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

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.