I'm only sending one request at a time. Why am I still getting 429?

Most likely multiple processes or services sharing the same API key. Check your CodeGateway request logs to find which service is consuming quota.

Is 529 worse than 429?

Neither is worse — both are temporary. 429 is your quota, wait retry-after. 529 is Anthropic-side load, clears in 30–60 seconds and has nothing to do with your quota.

What's the difference between rate_limit_error and overloaded_error?

rate_limit_error (429) means you sent too many requests — your quota is the issue. overloaded_error (529) is Anthropic's infrastructure under load — it can happen even when you're well under your quota. Fix for 529 is always exponential backoff. Summary Rate limits are manageable once you understand the three independent dimensions (RPM, TPD, concurrency) and respect the retry-after signal. The retry pattern above handles 95%+ of real-world rate limit scenarios without manual intervention. Tested in May 2026 using CodeGateway production request logs and the Anthropic Python SDK.

Claude API Rate Limits: RPM, TPD & Concurrency (2026)

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python

import anthropic
import time

client = anthropic.Anthropic(
    api_key="your-codegateway-key",
    base_url="https://api.codegateway.dev/v1"
)

def call_with_retry(prompt: str, max_retries: int = 5) -> str:
    for attempt in range(max_retries):
        try:
            response = client.messages.create(
                model="claude-sonnet-4-5",
                max_tokens=1024,
                messages=[{"role": "user", "content": prompt}]
            )
            return response.content[0].text
        except anthropic.RateLimitError as e:
            retry_after = int(e.response.headers.get("retry-after", 60))
            print(f"Rate limited, waiting {retry_after}s (attempt {attempt + 1})")
            time.sleep(retry_after)
        except anthropic.APIStatusError as e:
            if e.status_code == 529:
                wait = 30 * (2 ** attempt)
                print(f"Overloaded, waiting {wait}s")
                time.sleep(wait)
            else:
                raise
    raise RuntimeError("Max retries exceeded")

python

import asyncio
import anthropic

async def batch_process(prompts: list[str], max_concurrent: int = 5) -> list[str]:
    semaphore = asyncio.Semaphore(max_concurrent)
    client = anthropic.AsyncAnthropic(
        api_key="your-codegateway-key",
        base_url="https://api.codegateway.dev/v1"
    )
    
    async def single_call(prompt: str) -> str:
        async with semaphore:
            response = await client.messages.create(
                model="claude-sonnet-4-5",
                max_tokens=1024,
                messages=[{"role": "user", "content": prompt}]
            )
            return response.content[0].text
    
    return await asyncio.gather(*[single_call(p) for p in prompts])

python

import time

def rate_limited_batch(prompts: list[str], rpm_limit: int = 40) -> list[str]:
    interval = 60.0 / rpm_limit  # 20% headroom below the actual limit
    results = []
    for prompt in prompts:
        start = time.time()
        results.append(call_with_retry(prompt))
        elapsed = time.time() - start
        if elapsed < interval:
            time.sleep(interval - elapsed)
    return results

Claude API Rate Limits Explained: RPM, TPD & Concurrency (2026)

TL;DR

Why Does Rate Limiting Happen?

Anthropic's Rate Limit Tiers (2026)

Reading the Error Response

HTTP Status Codes

The 429 Response Headers

Retry Logic That Actually Works

Concurrency: The Limit Developers Miss Most

Engineering Techniques to Stay Under Limits

Rate Spreading

Token Budget Awareness

Using Claude API via CodeGateway

Common Questions

Summary