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

# Use the DeepSeek V4 API

> Access DeepSeek V4 Pro with a 1M context window for long document analysis, code generation, and multi-step reasoning. Curl, Python, and TypeScript examples.

export const RuncrateStyles = () => {
  if (typeof document !== 'undefined' && !document.getElementById('runcrate-overrides')) {
    const s = document.createElement('style');
    s.id = 'runcrate-overrides';
    s.textContent = `
      /* Match Runcrate's rounding scale (--radius: 0.75rem) */
      .rounded-sm { border-radius: 0.5rem !important; }   /* 8px */
      .rounded-md { border-radius: 0.625rem !important; } /* 10px */
      .rounded-lg { border-radius: 0.75rem !important; }  /* 12px */
      .rounded-l-sm { border-top-left-radius: 0.5rem !important; border-bottom-left-radius: 0.5rem !important; }
      .rounded-r-sm { border-top-right-radius: 0.5rem !important; border-bottom-right-radius: 0.5rem !important; }
      .rounded-l-md { border-top-left-radius: 0.625rem !important; border-bottom-left-radius: 0.625rem !important; }
      .rounded-r-md { border-top-right-radius: 0.625rem !important; border-bottom-right-radius: 0.625rem !important; }
      .rounded-l-lg { border-top-left-radius: 0.75rem !important; border-bottom-left-radius: 0.75rem !important; }
      .rounded-r-lg { border-top-right-radius: 0.75rem !important; border-bottom-right-radius: 0.75rem !important; }

      /* Cards: never pure white in light mode */
      .card { background-color: #fcfcfc !important; border-radius: 0.75rem !important; }
      html.dark .card { background-color: #141414 !important; }

      /* Docs hero box */
      .rc-hero { background-color: #fcfcfc; border: 1px solid #e0e0e0; }
      html.dark .rc-hero { background-color: #141414; border-color: #242424; }
      html.dark .rc-hero h1 { color: #f5f5f5; }

      /* Runcrate scrollbar — thin, transparent track, hide-until-hover thumb */
      ::-webkit-scrollbar { width: 6px; height: 6px; background-color: transparent; }
      ::-webkit-scrollbar-track { background-color: transparent; }
      ::-webkit-scrollbar-thumb { background-color: rgba(155, 155, 155, 0.5); border-radius: 10px; transition: opacity 0.3s ease; opacity: 0; }
      ::-webkit-scrollbar-thumb:hover { background-color: rgba(155, 155, 155, 0.7); }
      *:hover::-webkit-scrollbar-thumb,
      *:focus::-webkit-scrollbar-thumb,
      *:active::-webkit-scrollbar-thumb { opacity: 1; }
      * { scrollbar-width: thin; scrollbar-color: rgba(155, 155, 155, 0.5) transparent; }
    `;
    document.head.appendChild(s);
  }
  return null;
};

<RuncrateStyles />

DeepSeek V4 Pro offers a 1M token context window — enough to process entire codebases, full-length books, or hundreds of pages of legal contracts in a single request. Access it through the Runcrate Models API with no GPU management and no waitlists.

## Why DeepSeek V4 Pro

| Feature               | Detail                                                        |
| --------------------- | ------------------------------------------------------------- |
| **Context window**    | 1,000,000 tokens                                              |
| **Architecture**      | Mixture-of-Experts                                            |
| **Best for**          | Long document analysis, code generation, multi-step reasoning |
| **API compatibility** | OpenAI-compatible chat completions                            |

***

## Basic chat completion

<CodeGroup>
  ```bash curl theme={"theme":"github-dark"}
  curl https://api.runcrate.ai/v1/chat/completions \
    -H "Authorization: Bearer rc_live_YOUR_API_KEY" \
    -H "Content-Type: application/json" \
    -d '{
      "model": "deepseek-ai/DeepSeek-V4-Pro",
      "messages": [
        {"role": "user", "content": "Explain the mixture-of-experts architecture in three sentences."}
      ],
      "max_tokens": 512
    }'
  ```

  ```python Python theme={"theme":"github-dark"}
  from openai import OpenAI

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

  response = client.chat.completions.create(
      model="deepseek-ai/DeepSeek-V4-Pro",
      messages=[{"role": "user", "content": "Explain the mixture-of-experts architecture in three sentences."}],
      max_tokens=512,
  )
  print(response.choices[0].message.content)
  ```

  ```typescript TypeScript theme={"theme":"github-dark"}
  import OpenAI from "openai";

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

  const response = await client.chat.completions.create({
    model: "deepseek-ai/DeepSeek-V4-Pro",
    messages: [{ role: "user", content: "Explain the mixture-of-experts architecture in three sentences." }],
    max_tokens: 512,
  });

  console.log(response.choices[0].message.content);
  ```
</CodeGroup>

***

## Long document analysis (1M context)

The 1M context window means you can pass an entire document — a legal contract, research paper, or codebase — directly in the prompt. No chunking, no RAG pipeline, no lost context.

```python theme={"theme":"github-dark"}
from openai import OpenAI
from pathlib import Path

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

# Load a full document — a 200-page contract, a novel, a codebase dump
document = Path("contract.txt").read_text()

response = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-V4-Pro",
    messages=[
        {"role": "system", "content": "You are a legal analyst. Read the full contract and answer questions precisely, citing section numbers."},
        {"role": "user", "content": f"Here is the contract:\n\n{document}\n\nList every clause that limits liability, with the exact section number and a one-sentence summary of each."},
    ],
    max_tokens=4096,
)

print(response.choices[0].message.content)
```

***

## Streaming

Add `stream: true` to any request and iterate over chunks as they arrive. Works with the OpenAI SDK in both Python (`for chunk in stream`) and TypeScript (`for await ... of stream`).

***

## Next steps

* [Analyze long documents with AI](/examples/long-context-analysis) — compare 1M-context models side by side.
* [Extract structured data](/examples/structured-output) — combine DeepSeek V4 with schema-based extraction.
* [Model catalog](/models/model-catalog) — browse all available models and pricing.