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

# Clarke 1.0

> Sonnet-class inference. The production default for RAG, copilots and structured outputs

# Clarke 1.0

Clarke 1.0 is the production default. It serves RAG pipelines, copilots, code assistance and structured outputs at the quality level of a mid-tier frontier model. Use Clarke for any workload where you need reliability, speed and cost in balance.

## Model string

```
clarke-1.0
```

## Specs

| Spec | Value |
| - | - |
| Context window | 1,000,000 tokens |

<Note>
  Pricing is dynamic. For current rates see [radium.cloud/pricing](https://radium.cloud/pricing).
</Note>

## Capabilities

* Streaming: Supported
* Tool calling: Supported
* JSON mode: Supported
* JSON schema: Supported
* Reasoning: Supported
* Vision input: Supported

## Recommended use cases

* RAG and retrieval-augmented generation
* Coding copilots and autocomplete
* Structured JSON output from natural language
* Tool-calling agents
* Production chat and customer support

## Not suited for

Tasks that need deep reasoning over many steps, or very high-volume classification where every millisecond counts. Use Hal 1.0 or Tycho 1.0 for those.

## Example request

<CodeGroup>
  ```bash cURL theme={null}
  curl -X POST https://api.radium.cloud/v1/chat/completions \\
    -H "Authorization: Bearer $RADIUM_API_KEY" \\
    -H "Content-Type: application/json" \\
    -d '{
      "model": "clarke-1.0",
      "messages": [{"role": "user", "content": "Summarize this API changelog."}],
      "response_format": {"type": "json_object"}
    }'
  ```

  ```python Python theme={null}
  from openai import OpenAI
  client = OpenAI(api_key="YOUR_RADIUM_API_KEY", base_url="https://api.radium.cloud/v1")
  response = client.chat.completions.create(
      model="clarke-1.0",
      messages=[{"role": "user", "content": "Summarize this API changelog."}],
      response_format={"type": "json_object"},
  )
  print(response.choices[0].message.content)
  ```

  ```typescript TypeScript theme={null}
  import OpenAI from "openai";
  const client = new OpenAI({ apiKey: process.env.RADIUM_API_KEY, baseURL: "https://api.radium.cloud/v1" });
  const response = await client.chat.completions.create({
    model: "clarke-1.0",
    messages: [{ role: "user", content: "Summarize this API changelog." }],
    response_format: { type: "json_object" },
  });
  console.log(response.choices[0].message.content);
  ```
</CodeGroup>


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