> ## Documentation Index
> Fetch the complete documentation index at: https://student-213fb9fc.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Rate Limits

> Rate limits and usage quotas for AJ STUDIOZ Cloud Infra API plans

## Overview

AJ STUDIOZ Cloud Infra enforces rate limits to ensure fair access and platform stability. Limits apply per API key and are reset on a rolling or monthly basis depending on your plan.

***

## Rate Limit Headers

Every API response includes headers showing your current usage:

| Header                  | Description                                            |
| ----------------------- | ------------------------------------------------------ |
| `X-RateLimit-Limit`     | Maximum requests allowed in the window                 |
| `X-RateLimit-Remaining` | Requests remaining in the current window               |
| `X-RateLimit-Reset`     | Unix timestamp when the window resets                  |
| `Retry-After`           | Seconds to wait when rate limited (429 responses only) |

***

## Plan Limits

| Plan           | Requests / min | Tokens / day | Concurrent Requests |
| -------------- | -------------- | ------------ | ------------------- |
| **Free**       | 10             | 100K         | 2                   |
| **Developer**  | 60             | 1M           | 10                  |
| **Pro**        | 200            | 10M          | 30                  |
| **Enterprise** | Custom         | Custom       | Custom              |

<Note>Token limits apply across all models. Larger models consume more tokens per request.</Note>

***

## Rate Limit Errors

When you exceed your rate limit, the API returns a `429 Too Many Requests` response:

```json theme={null}
{
  "error": {
    "code": "rate_limit_exceeded",
    "message": "Rate limit exceeded. Please wait before retrying.",
    "retry_after": 30
  }
}
```

***

## Handling Rate Limits

### Python (with retry)

```python theme={null}
import time
import requests

def chat_with_retry(payload, max_retries=3):
    url = "https://api.ajstudioz.co.in/api/chat"
    headers = {"Authorization": "Bearer YOUR_API_KEY"}

    for attempt in range(max_retries):
        response = requests.post(url, json=payload, headers=headers)

        if response.status_code == 200:
            return response.json()
        elif response.status_code == 429:
            retry_after = int(response.headers.get("Retry-After", 10))
            print(f"Rate limited. Retrying in {retry_after}s...")
            time.sleep(retry_after)
        else:
            response.raise_for_status()

    raise Exception("Max retries exceeded")
```

### Python (with tenacity)

```python theme={null}
from tenacity import retry, stop_after_attempt, wait_exponential
from openai import OpenAI, RateLimitError

client = OpenAI(
    base_url="https://api.ajstudioz.co.in/v1",
    api_key="YOUR_API_KEY"
)

@retry(
    retry=lambda e: isinstance(e, RateLimitError),
    wait=wait_exponential(multiplier=1, min=2, max=60),
    stop=stop_after_attempt(5)
)
def get_completion(prompt: str) -> str:
    return client.chat.completions.create(
        model="gemma3:27b",
        messages=[{"role": "user", "content": prompt}]
    ).choices[0].message.content
```

***

## Best Practices

* **Batch requests** — combine multiple prompts where possible instead of making individual calls
* **Stream responses** — use streaming to get faster first tokens without increasing rate limit usage
* **Cache results** — cache identical prompts/responses to avoid redundant API calls
* **Use smaller models for dev** — use `gemma3:4b` or `gemma3:12b` during development to save quota
* **Monitor headers** — track `X-RateLimit-Remaining` to proactively back off before hitting limits

***

## Upgrade Your Plan

Need higher limits? [Upgrade at cloud.ajstudioz.com](https://cloud.ajstudioz.com/billing) or [contact us](mailto:support@ajstudioz.com) for Enterprise pricing.