Rate Limits & Quotas

Understanding and working within Claude API rate limits and usage quotas

title: Rate Limits & Quotas description: Understanding and working within Claude API rate limits and usage quotas

The Claude API implements rate limits to ensure fair usage and system stability. This guide explains how limits work and strategies to optimize your usage.

Rate Limit Types

Request Limits

| Tier | Requests Per Minute (RPM) | |------|---------------------------| | Free | 5 | | Build | 50 | | Scale | 1,000 | | Enterprise | Custom |

Token Limits

| Tier | Tokens Per Minute (TPM) | Tokens Per Day (TPD) | |------|-------------------------|----------------------| | Free | 20,000 | 300,000 | | Build | 100,000 | 2,500,000 | | Scale | 400,000 | 10,000,000 | | Enterprise | Custom | Custom |

Model-Specific Limits

Different models may have different limits:

| Model | Max Context | Max Output | |-------|-------------|------------| | Claude Opus 4 | 200K | 8,192 | | Claude Sonnet 4 | 200K | 8,192 | | Claude 3.5 Haiku | 200K | 8,192 |

Understanding Rate Limit Headers

Every API response includes rate limit information:

Accessing Headers

Handling Rate Limits

Basic Rate Limit Handler

Token-Based Rate Limiting

Request Queuing

Simple Queue Implementation

Optimizing Token Usage

Prompt Compression

Reduce token usage by being concise:

Response Length Control

Set appropriate max_tokens:

Context Window Management

Trim conversation history to stay within limits:

Model Selection for Cost Optimization

Choose the appropriate model for the task:

| Task Type | Recommended Model | Rationale | |-----------|-------------------|-----------| | Simple Q&A | Haiku | Fast, cheap | | Code review | Sonnet | Good balance | | Complex analysis | Opus | Highest capability | | High volume | Haiku/Sonnet | Cost effective |

Monitoring Usage

Usage Tracking

Best Practices

1. Implement backoff - Always use exponential backoff for retries

2. Monitor headers - Track remaining limits in responses

3. Batch when possible - Reduce request overhead

4. Use appropriate models - Don't use Opus for simple tasks

5. Set max_tokens appropriately - Don't request more than needed

6. Compress prompts - Remove unnecessary verbosity

7. Manage conversation length - Trim history to stay within limits

8. Plan for scale - Consider upgrading tiers for production

Tier Upgrades

If you're hitting limits regularly:

1. Build tier - For development and small-scale production
2. Scale tier - For production applications
3. Enterprise - For custom limits and SLAs

Visit console.anthropic.com↗ to manage your tier.

Next Steps

• Error handling
• Streaming responses
• Model comparison