Rate Limits ↗

To mitigate misuse and manage capacity on the API, limits are in place on how much an organization can use the Claude API.

There are two types of limits:

1. Spend limits set a maximum monthly cost an organization can incur for API usage.
2. Rate limits set the maximum number of API requests an organization can make over a defined period of time.

The API enforces service-configured limits at the organization level, but you may also set user-configurable limits for your organization’s workspaces.

These limits apply to both Standard and Priority Tier usage. For more information about Priority Tier, which offers enhanced service levels in exchange for committed spend, see Service Tiers.

About rate limits#

• Limits are designed to prevent API abuse, while minimizing impact on common customer usage patterns.
• Limits are defined by usage tier, where each tier is associated with a different set of spend and rate limits.
• Your organization will increase tiers automatically as you reach certain thresholds while using the API. Limits are set at the organization level. You can see your organization’s limits in the Limits page in the Claude Console.
• You may hit rate limits over shorter time intervals. For instance, a rate of 60 requests per minute (RPM) may be enforced as 1 request per second. Short bursts of requests at a high volume can surpass the rate limit and result in rate limit errors.
• The limits outlined below are the standard tier limits. If you’re seeking higher, custom limits or Priority Tier for enhanced service levels, contact sales through the Claude Console.
• The API uses the token bucket algorithm to do rate limiting. This means that your capacity is continuously replenished up to your maximum limit, rather than being reset at fixed intervals.
• All limits described here represent maximum allowed usage, not guaranteed minimums. These limits are intended to reduce unintentional overspend and ensure fair distribution of resources among users.

Spend limits#

Each usage tier has a limit on how much you can spend on the API each calendar month. Once you reach the spend limit of your tier, until you qualify for the next tier, you will have to wait until the next month to be able to use the API again.

To qualify for the next tier, you must meet a deposit requirement. To minimize the risk of overfunding your account, you cannot deposit more than your monthly spend limit.

Requirements to advance tier#

Credit Purchase shows the cumulative credit purchases (excluding tax) required to advance to that tier. You advance immediately upon reaching the threshold.

Max Credit Purchase limits the maximum amount you can add to your account in a single transaction to prevent account overfunding.

Rate limits#

The rate limits for the Messages API are measured in requests per minute (RPM), input tokens per minute (ITPM), and output tokens per minute (OTPM) for each model class. If you exceed any of the rate limits you will get a 429 error describing which rate limit was exceeded, along with a retry-after header indicating how long to wait.

You might also encounter 429 errors due to acceleration limits on the API if your organization has a sharp increase in usage. To avoid hitting acceleration limits, ramp up your traffic gradually and maintain consistent usage patterns.

Cache-aware ITPM#

Many API providers use a combined “tokens per minute” (TPM) limit that may include all tokens, both cached and uncached, input and output. For most Claude models, only uncached input tokens count towards your ITPM rate limits. This is a key advantage that makes the rate limits effectively higher than they might initially appear.

ITPM rate limits are estimated at the beginning of each request, and the estimate is adjusted during the request to reflect the actual number of input tokens used.

Here’s what counts towards ITPM:

• input_tokens (tokens after the last cache breakpoint) ✓ Count towards ITPM
• cache_creation_input_tokens (tokens being written to cache) ✓ Count towards ITPM
• cache_read_input_tokens (tokens read from cache) ✗ Do NOT count towards ITPM for most models

The input_tokens field only represents tokens that appear after your last cache breakpoint, not all input tokens in your request. To calculate total input tokens:

total_input_tokens = cache_read_input_tokens + cache_creation_input_tokens + input_tokens

This means when you have cached content, input_tokens will typically be much smaller than your total input. For example, with a 200K token cached document and a 50 token user question, you’d see input_tokens: 50 even though the total input is 200,050 tokens.

For rate limit purposes on most models, only input_tokens + cache_creation_input_tokens count toward your ITPM limit, making prompt caching an effective way to increase your effective throughput.

Example: With a 2,000,000 ITPM limit and an 80% cache hit rate, you could effectively process 10,000,000 total input tokens per minute (2M uncached + 8M cached), since cached tokens don’t count towards your rate limit.

Some older models (marked with † in the rate limit tables below) also count cache_read_input_tokens towards ITPM rate limits.

For all models without the † marker, cached input tokens do not count towards rate limits and are billed at a reduced rate (10% of base input token price). This means you can achieve significantly higher effective throughput by using prompt caching.

Maximize your rate limits with prompt caching

To get the most out of your rate limits, use prompt caching for repeated content like:

• System instructions and prompts
• Large context documents
• Tool definitions
• Conversation history

With effective caching, you can dramatically increase your actual throughput without increasing your rate limits. Monitor your cache hit rate on the Usage page to optimize your caching strategy.

OTPM rate limits are evaluated in real time as output tokens are produced, counting only the actual tokens generated. The max_tokens parameter does not factor into OTPM rate limit calculations, so there is no rate limit downside to setting a higher max_tokens value.

Rate limits are applied separately for each model; therefore you can use different models up to their respective limits simultaneously. You can check your current rate limits and behavior in the Claude Console.

Rate limits are currently shared across all inference_geo values. Requests with inference_geo: "us" and inference_geo: "global" draw from the same rate limit pool.

For long context requests (>200K tokens) when using the context-1m-2025-08-07 beta header with Claude Opus 4.x or Sonnet 4.x, separate rate limits apply. See Long context rate limits below.

If you’re seeking higher limits for an Enterprise use case, contact sales through the Claude Console.

^{* - Opus rate limit is a total limit that applies to combined traffic across Opus 4.6, Opus 4.5, Opus 4.1, and Opus 4.}

^{** - Sonnet 4.x rate limit is a total limit that applies to combined traffic across Sonnet 4.6, Sonnet 4.5, and Sonnet 4.}

^{† - Limit counts cache_read_input_tokens towards ITPM usage.}

Message Batches API#

The Message Batches API has its own set of rate limits which are shared across all models. These include a requests per minute (RPM) limit to all API endpoints and a limit on the number of batch requests that can be in the processing queue at the same time. A “batch request” here refers to part of a Message Batch. You may create a Message Batch containing thousands of batch requests, each of which count towards this limit. A batch request is considered part of the processing queue when it has yet to be successfully processed by the model.

Fast mode rate limits#

When using fast mode (speed: "fast") on Opus 4.6 (research preview), dedicated rate limits apply that are separate from standard Opus rate limits. When fast mode rate limits are exceeded, the API returns a 429 error with a retry-after header.

The response includes anthropic-fast-* headers that indicate your fast mode rate limit status. See the fast mode documentation for details on these headers.

Long context rate limits#

When using Claude Opus 4.6, Sonnet 4.6, Sonnet 4.5, or Sonnet 4 with the 1M token context window enabled, the following dedicated rate limits apply to requests exceeding 200K tokens.

The 1M token context window is currently in beta for organizations in usage tier 4 and organizations with custom rate limits. The 1M token context window is only available for Claude Opus 4.6, Sonnet 4.6, Sonnet 4.5, and Sonnet 4.

To get the most out of the 1M token context window with rate limits, use prompt caching.

Monitoring your rate limits in the Console#

You can monitor your rate limit usage on the Usage page of the Claude Console.

In addition to providing token and request charts, the Usage page provides two separate rate limit charts. Use these charts to see what headroom you have to grow, when you may be hitting peak use, better undersand what rate limits to request, or how you can improve your caching rates. The charts visualize a number of metrics for a given rate limit (e.g. per model):

• The Rate Limit - Input Tokens chart includes:
  • Hourly maximum uncached input tokens per minute
  • Your current input tokens per minute rate limit
  • The cache rate for your input tokens (i.e. the percentage of input tokens read from the cache)
• The Rate Limit - Output Tokens chart includes:
  • Hourly maximum output tokens per minute
  • Your current output tokens per minute rate limit

Setting lower limits for Workspaces#

For more about workspaces, see Workspaces.

In order to protect Workspaces in your Organization from potential overuse, you can set custom spend and rate limits per Workspace.

Example: If your Organization’s limit is 40,000 input tokens per minute and 8,000 output tokens per minute, you might limit one Workspace to 30,000 total tokens per minute. This protects other Workspaces from potential overuse and ensures a more equitable distribution of resources across your Organization. The remaining unused tokens per minute (or more, if that Workspace doesn’t use the limit) are then available for other Workspaces to use.

Note:

• You can’t set limits on the default Workspace.
• If not set, Workspace limits match the Organization’s limit.
• Organization-wide limits always apply, even if Workspace limits add up to more.
• Support for input and output token limits will be added to Workspaces in the future.

Response headers#

The API response includes headers that show you the rate limit enforced, current usage, and when the limit will be reset.

The following headers are returned:

The anthropic-ratelimit-tokens-* headers display the values for the most restrictive limit currently in effect. For instance, if you have exceeded the Workspace per-minute token limit, the headers will contain the Workspace per-minute token rate limit values. If Workspace limits do not apply, the headers will return the total tokens remaining, where total is the sum of input and output tokens. This approach ensures that you have visibility into the most relevant constraint on your current API usage.