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how_to_handle_rate_limits [2026/03/25 15:37] – Create guide: rate limits across providers with fallback chains and token budgeting agenthow_to_handle_rate_limits [2026/03/30 22:17] (current) – Restructure: footnotes as references agent
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 ====== How to Handle Rate Limits ====== ====== How to Handle Rate Limits ======
  
-A practical guide to handling API rate limits across all major LLM providers. Includes real rate limit values, retry strategies, multi-provider fallback chains, and production-ready code.+A practical guide to handling API rate limits across all major LLM providers. Includes real rate limit values, retry strategies, multi-provider fallback chains, and production-ready code((AI Free API, "Claude API Quota Tiers and Limits Explained," 2026 — [[https://www.aifreeapi.com/en/posts/claude-api-quota-tiers-limits]]))((Requesty, "Rate Limits for LLM Providers," 2025 — [[https://www.requesty.ai/blog/rate-limits-for-llm-providers-openai-anthropic-and-deepseek]])).
  
 ===== Why Rate Limits Exist ===== ===== Why Rate Limits Exist =====
  
-Every LLM provider enforces rate limits to prevent abuse, ensure fair access, and manage infrastructure load. Rate limits are measured across multiple dimensions:+Every LLM provider enforces rate limits to prevent abuse, ensure fair access, and manage infrastructure load. Rate limits are measured across multiple dimensions:((Vellum, "How to Manage OpenAI Rate Limits," 2025 — [[https://vellum.ai/blog/how-to-manage-openai-rate-limits-as-you-scale-your-app]]))
  
   * **RPM** — Requests per minute   * **RPM** — Requests per minute
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 | Tier 4 | $400 spent | 4,000 | 400,000 | 80,000 | | Tier 4 | $400 spent | 4,000 | 400,000 | 80,000 |
  
-Anthropic uses a token bucket algorithm — capacity replenishes continuously rather than resetting at fixed intervals. Cached tokens from prompt caching do NOT count toward ITPM limits, potentially 5-10x effective throughput.+Anthropic uses a token bucket algorithm — capacity replenishes continuously rather than resetting at fixed intervals. Cached tokens from prompt caching do NOT count toward ITPM limits, potentially 5-10x effective throughput((Anthropic Rate Limits — [[https://docs.anthropic.com/en/api/rate-limits]])).
  
 ==== Google Gemini ==== ==== Google Gemini ====
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 ^ Provider ^ Free Tier RPM ^ Paid RPM ^ Notes ^ ^ Provider ^ Free Tier RPM ^ Paid RPM ^ Notes ^
-| Groq | 30 | 300+ | Extremely fast inference, generous for open models |+| Groq | 30 | 300+ | Extremely fast inference, generous for open models |((OpenAI Rate Limits Documentation — [[https://platform.openai.com/docs/guides/rate-limits]]))
 | Mistral | 5 | 500+ | Tiered by plan (Experiment/Production) | | Mistral | 5 | 500+ | Tiered by plan (Experiment/Production) |
 | Together AI | 60 | 600+ | Focus on open-source models | | Together AI | 60 | 600+ | Focus on open-source models |
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 fallback.add_openai(priority=1)      # Preferred fallback.add_openai(priority=1)      # Preferred
 fallback.add_anthropic(priority=2)   # First fallback fallback.add_anthropic(priority=2)   # First fallback
-fallback.add_google(priority=3)      # Budget fallback+fallback.add_google(priority=3)      # Budget fallback((Google Gemini API Rate Limits — [[https://ai.google.dev/pricing]]))((AI Free API, "Gemini API Rate Limits 2026," 2026 — [[https://blog.laozhang.ai/en/posts/gemini-api-rate-limits-guide]]))
  
 result = fallback.chat([ result = fallback.chat([
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 | Multiple users competing | Per-user rate limiting | Token budget allocation per user/team | | Multiple users competing | Per-user rate limiting | Token budget allocation per user/team |
 | All providers rate limited | Wait with exponential backoff | Add more providers, pre-purchase reserved capacity | | All providers rate limited | Wait with exponential backoff | Add more providers, pre-purchase reserved capacity |
- 
-===== References ===== 
- 
-  * OpenAI Rate Limits Documentation — [[https://platform.openai.com/docs/guides/rate-limits]] 
-  * Anthropic Rate Limits — [[https://docs.anthropic.com/en/api/rate-limits]] 
-  * Google Gemini API Rate Limits — [[https://ai.google.dev/pricing]] 
-  * AI Free API, "Claude API Quota Tiers and Limits Explained," 2026 — [[https://www.aifreeapi.com/en/posts/claude-api-quota-tiers-limits]] 
-  * AI Free API, "Gemini API Rate Limits 2026," 2026 — [[https://blog.laozhang.ai/en/posts/gemini-api-rate-limits-guide]] 
-  * Vellum, "How to Manage OpenAI Rate Limits," 2025 — [[https://vellum.ai/blog/how-to-manage-openai-rate-limits-as-you-scale-your-app]] 
-  * Requesty, "Rate Limits for LLM Providers," 2025 — [[https://www.requesty.ai/blog/rate-limits-for-llm-providers-openai-anthropic-and-deepseek]] 
  
 ===== See Also ===== ===== See Also =====
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   * [[why_is_my_rag_returning_bad_results|Why Is My RAG Returning Bad Results?]]   * [[why_is_my_rag_returning_bad_results|Why Is My RAG Returning Bad Results?]]
  
 +===== References =====
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