Google Vertex AI (generative AI) error
Vertex AI: "429 Too many requests. Exceeded the Provisioned Throughput": what it means and how to fix it
429 Too many requests. Exceeded the Provisioned Throughput.Retry? Not statedLast verified 2 documented fixes2 sources
What it means
The 429 message returned on the Provisioned Throughput quota framework when requests exceed the reserved capacity. Frequent errors usually mean you have exceeded your purchased capacity, so retries alone may not solve it.
Causes
- Usage exceeds the purchased Provisioned Throughput capacity
How to fix it
- Fix 1.
Use the default behavior (no Provisioned Throughput header in prediction requests) so overages are processed on demand and billed as pay-as-you-go.
- Fix 2.
Increase the number of GSUs in your Provisioned Throughput subscription.
More Vertex AI errors
All 11 Vertex AI errorsHTTP 429 at other providers
Compare 429 across providers429 ThrottlingExceptionRetry? YesAmazon Bedrock429 ModelNotReadyExceptionRetry? YesAmazon Bedrock429 rate_limit_errorRetry? YesAnthropic API429 rate_limit_error (enforced_spend_limit_reached)Retry? NoAnthropic API429 Too Many Requests (Rate limit is exceeded)Retry? YesAzure OpenAI429 Too Many Requests (System is experiencing high demand)Retry? YesAzure OpenAI429 Too Many Requests (temporary rate limit adjustment)Retry? YesAzure OpenAI429 Too Many Requests (token budget exceeded by request parameters)Retry? Not statedAzure OpenAI429 Too Many RequestsRetry? YesCohere API429 - Rate Limit ReachedRetry? Not statedDeepSeek API429 rate_limit_exceededRetry? YesGemini API429 quota_exceededRetry? YesGemini API
FAQ
What does the Vertex AI error "429 Too many requests. Exceeded the Provisioned Throughput" mean?
The 429 message returned on the Provisioned Throughput quota framework when requests exceed the reserved capacity. Frequent errors usually mean you have exceeded your purchased capacity, so retries alone may not solve it.
How do I fix Vertex AI "429 Too many requests. Exceeded the Provisioned Throughput"?
There are 2 documented fixes. Start with the first: Use the default behavior (no Provisioned Throughput header in prediction requests) so overages are processed on demand and billed as pay-as-you-go.
Should I retry Vertex AI "429 Too many requests. Exceeded the Provisioned Throughput"?
Not stated. The official docs do not say whether this error is retryable.
Which other AI APIs return HTTP 429?
Per their official error docs: Amazon Bedrock (429 ThrottlingException; 429 ModelNotReadyException), Anthropic API (429 rate_limit_error; 429 rate_limit_error (enforced_spend_limit_reached)), Azure OpenAI (429 Too Many Requests (Rate limit is exceeded); 429 Too Many Requests (System is experiencing high demand); 429 Too Many Requests (temporary rate limit adjustment); 429 Too Many Requests (token budget exceeded by request parameters)), Cohere API (429 Too Many Requests), DeepSeek API (429 - Rate Limit Reached), Gemini API (429 rate_limit_exceeded; 429 quota_exceeded; 429 too_many_requests; 429 RESOURCE_EXHAUSTED), Groq API (429 Too Many Requests), Mistral API (429 Too many requests), OpenAI API (429 credit_balance_exhausted; 429 Rate limit reached for requests; 429 rate_limit_error slow_down; 429 organization_spend_limit_exceeded; 429 project_spend_limit_exceeded; 429 organization_usage_limit_exceeded), OpenRouter (429 rate_limit_exceeded), xAI API (429 Too Many Requests).
Sources
Last verified against 2 sources: Vertex AI's official docs and official SDK repositories.
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