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Authentication errors
401 invalid or missing credential
The bearer token is missing, malformed, or has been revoked.
Fix: Check that NEON_AI_GATEWAY_TOKEN is set and contains the full nt_live_... token returned when you created the credential. If the credential was revoked, create a new one. See Authentication.
403 credential not authorized for ai gateway
The credential exists but lacks the ai_gateway:invoke scope.
Fix: Create a new credential that includes ai_gateway:invoke in the scopes array. You can't add scopes to an existing credential. See Authentication.
403 credential not authorized for this branch
The credential was issued on a branch that is not an ancestor of the branch in the request hostname.
Fix: Use a credential issued on the current branch or an ancestor branch. See Authentication for how branch lineage works.
503 authorization temporarily unavailable
The credential store or branch resolver is temporarily unavailable.
Fix: Retry the request. This is a transient infrastructure error, not a client error.
Model errors
400 unknown model
The model field in the request body does not match any entry in the AI Gateway catalog.
Fix: Check the model ID against the full model catalog. Use the short form (e.g., claude-sonnet-4-6) or the databricks- prefixed form (databricks-claude-sonnet-4-6) — both are accepted.
400 model is not available on this endpoint
The model exists in the catalog but doesn't work with the endpoint you're calling.
Fix: Check which endpoint the model requires:
- Anthropic models (
claude-*) on/openai/v1/responses→ use/anthropic/v1/messagesor/mlflow/v1/chat/completions - OpenAI codex models on
/mlflow/v1/chat/completions→ use/openai/v1/responses - Google models on
/anthropic/v1/messages→ use/gemini/v1beta/...or/mlflow/v1/chat/completions
400 missing or invalid model
The request body does not contain a valid model field.
Fix: Include "model": "<model-id>" in the request body.
Gemini-specific errors
404 unsupported gemini action
The action in the Gemini endpoint URL is not generateContent.
Fix: Only generateContent is supported. The URL must end with :<model-id>:generateContent. Other actions (countTokens, streamGenerateContent, etc.) are not available.
404 invalid gemini model path
The {modelAction} segment in the Gemini URL path is malformed. It must follow the format <model>:<action> where both parts are non-empty.
Fix: Ensure the URL path contains exactly one colon separating the model ID and action, e.g. gemini-2-5-flash:generateContent.
Workspace resolution errors
403or400:could not resolve workspace from host
The request host does not match the expected format or region.
Common causes:
- The host does not end with a trusted suffix (
.neon.techin production). Returns 403. - The host has no parseable AWS region label. Returns 400.
- The region in the host has no configured workspace. Returns 404.
Fix: Verify that you are using the correct AI Gateway host from the Neon Console or API. The host format for production is <branch-id>-api.<cell>.<region>.aws.neon.tech. Do not construct the host manually.
Rate limiting and quota
429: upstream provider rate limit
The request hit the upstream Databricks/provider rate limit.
Fix: Implement exponential backoff. The response includes a Retry-After header and provider-specific rate limit headers (X-Ratelimit-*, Anthropic-Ratelimit-*). See Rate limiting.
429: account quota exceeded
Your account's AI Gateway quota is blocked. The response body is:
{
"error_code": "REQUEST_LIMIT_EXCEEDED",
"message": "ai gateway quota exceeded"
}Fix: Check the Retry-After header. If present, the block is temporary and will lift at that time. If absent, the block is permanent until resolved. Contact support for a quota increase or to resolve a permanent block. See Rate limits for current quota values.
Upstream errors
502 upstream request failed
The gateway could not reach the upstream Databricks workspace, or the upstream returned an unexpected error.
Fix: Retry the request. If the error persists, check the Neon status page.
Error response formats
Most AI Gateway errors use the standard OpenAI error envelope:
{
"error": {
"message": "unknown model"
}
}The quota block error uses a different shape:
{
"error_code": "REQUEST_LIMIT_EXCEEDED",
"message": "ai gateway quota exceeded"
}Need help?
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