The API enforces service-configured limits at the organization level, but you may also set user-configurable limits for your…
Anthropic Rate Limits → · 2026-10-21T19:20:32.467Z
- The API enforces service-configured limits at the organization level, but you may also set user-configurable limits for your organization's workspaces. + The API enforces service-configured limits at the organization level, but you can also set user-configurable limits for your organization's workspaces. - When usage reaches a spend limit you set, requests return HTTP 400 with error type `invalid_request_error`. The message begins `You have reached your specified API usage limits`, or `You have reached your specified workspace API usage limits` for a workspace limit, and states when access resumes. Raise or remove the limit to restore access sooner. + When usage reaches a spend limit you set, requests return HTTP 400 with error type `invalid_request_error`. The message starts with `You have reached your specified API usage limits`, or `You have reached your specified workspace API usage limits` for a workspace limit, and states when access resumes. Raise or remove the limit to restore access sooner. - 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](https://docs.anthropic.com/docs/en/api/errors) + 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](https://docs.anthropic.com/docs/en/api/errors) - 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 toward your ITPM rate limits.** This is a key advantage that makes the rate limits effectively higher than they might initially appear. + Many API providers use a combined "tokens per minute" (TPM) limit that might include all tokens, both cached and uncached, input and output. **For most Claude models, only uncached input tokens count toward your ITPM rate limits.** This is a key advantage that makes the rate limits effectively higher than they might initially appear. - **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), because cached tokens don't count toward your rate limit. + **Example:** With a 2,000,000 ITPM limit and an 80 percent cache hit rate, you could effectively process 10,000,000 total input tokens per minute (2M uncached + 8M cached), because cached tokens don't count toward your rate limit. - To make the most of your rate limits, cache repeated content such as system instructions and prompts, large context documents, tool definitions, and conversation history; see [prompt caching](https://docs.anthropic.com/docs/en/build-with-claude/prompt-caching) - for guidance. With effective caching, you can substantially increase your actual throughput without raising your rate limits. Monitor your cache hit rate on the [Usage page](https://docs.anthropic.com/usage) - in the Claude Console to tune your caching strategy. + To get the highest throughput within your rate limits, cache repeated content such as system instructions and prompts, large context documents, tool definitions, and conversation history; see [prompt caching](https://docs.anthropic.com/docs/en/build-with-claude/prompt-caching) + for guidance. With effective caching, you can substantially increase your actual throughput without raising your rate limits. Monitor your cache hit rate on the [Usage](https://docs.anthropic.com/usage) + page in the Claude Console to tune your caching strategy. - 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 toward this limit. A batch request is considered part of the processing queue when it has yet to be successfully processed by the model. + 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 can create a Message Batch containing thousands of batch requests, each of which counts toward this limit. A batch request is considered part of the processing queue when it has yet to be successfully processed by the model. - endpoints are rate-limited per organization. These limits are separate from the Messages API rate limits above. + endpoints are rate-limited for each organization. These limits are separate from the Messages API rate limits described earlier on this page. - 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, identify when you may be hitting peak use, understand what rate limits to request, and learn how to improve your caching rates. The charts visualize a number of metrics for a given rate limit (for example, per model): + 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, identify when you might be hitting peak use, understand what rate limits to request, and learn how to improve your caching rates. The charts visualize a number of metrics for a given rate limit (for example, for each model): - Setting lower limits for Workspaces + Setting lower limits for workspaces - To protect Workspaces in your Organization from potential overuse, you can set custom spend and rate limits per Workspace. + To protect Workspaces in your Organization from potential overuse, you can set custom spend and rate limits for each Workspace. - * Workspace limits are set per limiter type (such as requests per minute, input tokens per minute, or output tokens per minute). + * Workspace limits are set for each limiter type (such as requests per minute, input tokens per minute, or output tokens per minute).