Rate limits
Request rate limits by tier, ad-supported model spend limits, payload size limits, what happens when you hit a limit, and how to request more.
Generation rate limits
Rate limits for model inference requests depend on your account tier:
| Tier | Requests per minute (RPM) |
|---|---|
| Free | 30 |
| Paid (Growth, Enterprise) | 1,000 |
| Custom teams | Operator-managed per-team overrides |
Free-tier teams granted free credits by an operator are raised to 200 RPM, and keep that limit until an operator removes it; it does not expire when the credits run out. The pay-as-you-go credit-purchase floor is 250 RPM, so a real purchase always buys more headroom than a free grant. Per-team overrides for custom teams are configured by an operator; contact us to request one.
Batch API rate limits
Batch processing rate limits are separate from generation rate limits. See the Batch API for details.
Ad-supported model spend limits
Ad-supported models (for example moonshotai/kimi-k3.1-pro-with-ads) have two spend
limits on top of the generation rate limit:
- an hourly limit shared by all users of ad-supported models;
- a daily limit for each user (or each team, for requests without a user).
Both reset at the start of the UTC hour or day. Once either is reached, requests
to ad-supported models return HTTP 429 with error type
GravityAdsDiscountCap, a message naming the limit and when it resets, and a
Retry-After header. Standard models are not affected, so you can switch to the
standard model instead.
Payload size limits
- Request body: up to 32 MiB (33,554,432 bytes), including inline images.
Larger requests are rejected with HTTP
413. - Non-streaming response body: up to 32 MiB. A provider response larger
than that is refused with HTTP
502and error typeUpstreamResponseTooLarge. Usestream: true, or smaller batches for embeddings, to stay under it.
When you hit a limit
You receive a 429 Too Many Requests response. Back off and retry with
exponential backoff.
Increase your limits
If you need higher rate limits, contact support, use the support chat, or talk to the team about a custom tier.