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

# Understanding Inferoute Rate Limits

> Learn how Inferoute enforces per-key rate limits, read limit headers in API responses, and handle 429 errors with exponential backoff.

Inferoute enforces rate limits on every API key to ensure fair usage across all customers and to protect system stability. Limits are measured in requests per minute (RPM) and tokens per minute (TPM). When you exceed a limit, the API returns a `429 Too Many Requests` response until the window resets.

## Default limit tiers

| Plan       | Requests per minute (RPM) | Tokens per minute (TPM) |
| ---------- | ------------------------- | ----------------------- |
| Free       | 60                        | 100,000                 |
| Pro        | 600                       | 1,000,000               |
| Enterprise | Custom                    | Custom                  |

Contact [support@inferoute.ai](mailto:support@inferoute.ai) to request a limit increase for your plan.

## Rate limit headers

Every API response includes headers that tell you your current limit status:

| Header                           | Description                                               |
| -------------------------------- | --------------------------------------------------------- |
| `X-RateLimit-Limit-Requests`     | Maximum number of requests allowed in the current window. |
| `X-RateLimit-Remaining-Requests` | Number of requests remaining before you hit the limit.    |
| `X-RateLimit-Reset-Requests`     | Unix timestamp (seconds) when the request window resets.  |

## Handling 429 errors

When you exceed your rate limit, the API responds with:

```
HTTP/1.1 429 Too Many Requests
Retry-After: 15
```

The `Retry-After` header tells you the number of seconds to wait before retrying. The safest strategy is **exponential backoff with jitter** — wait progressively longer between retries, with a small random component to avoid synchronized retry storms.

<CodeGroup>
  ```python python theme={null}
  import time
  import random
  import openai

  client = openai.OpenAI(
      base_url="https://api.inferoute.ai/v1",
      api_key="YOUR_INFEROUTE_API_KEY",
  )

  def chat_with_backoff(**kwargs):
      max_retries = 5
      base_delay = 1  # seconds

      for attempt in range(max_retries):
          try:
              return client.chat.completions.create(**kwargs)
          except openai.RateLimitError as e:
              if attempt == max_retries - 1:
                  raise
              delay = base_delay * (2 ** attempt) + random.uniform(0, 1)
              print(f"Rate limit hit. Retrying in {delay:.2f}s...")
              time.sleep(delay)

  response = chat_with_backoff(
      model="gpt-4o",
      messages=[{"role": "user", "content": "Hello!"}],
  )
  ```

  ```javascript node.js theme={null}
  import OpenAI from "openai";

  const client = new OpenAI({
    baseURL: "https://api.inferoute.ai/v1",
    apiKey: process.env.INFEROUTE_API_KEY,
  });

  async function chatWithBackoff(params, maxRetries = 5) {
    let baseDelay = 1000; // milliseconds

    for (let attempt = 0; attempt < maxRetries; attempt++) {
      try {
        return await client.chat.completions.create(params);
      } catch (err) {
        if (err.status !== 429 || attempt === maxRetries - 1) throw err;
        const delay = baseDelay * Math.pow(2, attempt) + Math.random() * 1000;
        console.log(`Rate limit hit. Retrying in ${(delay / 1000).toFixed(2)}s...`);
        await new Promise((resolve) => setTimeout(resolve, delay));
      }
    }
  }

  const response = await chatWithBackoff({
    model: "gpt-4o",
    messages: [{ role: "user", content: "Hello!" }],
  });
  ```
</CodeGroup>

<Note>
  Inferoute rate limits are separate from any limits enforced by the underlying providers. Even if you are within your Inferoute limits, a provider may throttle the request on their end. Inferoute will surface those errors with the same `429` status code and attempt automatic retries according to your routing configuration.
</Note>