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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.

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.

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Why DeepSeek V4 Pro

FeatureDetail
Context window1,000,000 tokens
ArchitectureMixture-of-Experts
Best forLong document analysis, code generation, multi-step reasoning
API compatibilityOpenAI-compatible chat completions

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Basic chat completion

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
  }'

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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. 
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)

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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).

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Next steps