Rate Limits

The Impulse Labs API enforces a sliding window rate limit per user per 60-second period.

Limits by plan

Plan	Requests / 60 seconds
Pro	120
Team	300
Enterprise	1 000

Limits apply to validated inference requests — each call to POST /infer counts as one request against your limit.

Rate limit headers

Every response from POST /infer includes these headers:

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

Reading headers

curl -si -X POST "https://inference.impulselabs.ai/infer" \
  -H "Authorization: Bearer $IMPULSE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"deployment_id": "my-model", "inputs": {}}' \
  | grep -i x-ratelimit

# X-RateLimit-Limit: 120
# X-RateLimit-Remaining: 118
# X-RateLimit-Reset: 1708346460

Handling 429 Too Many Requests

When you exceed the limit, the API returns:

HTTP/1.1 429 Too Many Requests
Retry-After: 34
X-RateLimit-Limit: 120
X-RateLimit-Remaining: 0
X-RateLimit-Reset: 1708346460

{
  "valid": false,
  "error": "Rate limit exceeded",
  "limit": 120,
  "retry_after_seconds": 34
}

Recommended retry strategy

Read the Retry-After header and wait that many seconds before retrying.
Do not retry immediately in a tight loop — this will keep triggering the limit.
For batch workloads, spread requests over time or use exponential backoff.

Python — respect Retry-After

import time, requests

def safe_infer(session, payload, headers):
    while True:
        resp = session.post(
            "https://inference.impulselabs.ai/infer",
            json=payload,
            headers=headers,
        )
        if resp.status_code == 429:
            wait = int(resp.headers.get("Retry-After", 5))
            print(f"Rate limited. Retrying in {wait}s...")
            time.sleep(wait)
            continue
        resp.raise_for_status()
        return resp.json()

Upgrading your plan

If you consistently hit rate limits, consider upgrading to a higher plan at app.impulselabs.ai/billing. For custom limits or Enterprise pricing, contact us.

API Keys

Inference

Reference

Limits by plan

Rate limit headers

Reading headers

Handling 429 Too Many Requests

Recommended retry strategy

Upgrading your plan

​Limits by plan

​Rate limit headers

​Reading headers

​Handling 429 Too Many Requests

​Recommended retry strategy

​Upgrading your plan

Limits by plan

Rate limit headers

Reading headers

Handling 429 Too Many Requests

Recommended retry strategy

Upgrading your plan