Moonshot AI API errors explained: codes, causes and fixes

Diagnose a failed Kimi API request from its actual error type and account scope. Keep authentication, permission, billing, request shape and service pressure as separate investigations.

Error format at Moonshot

Kimi returns an error object with type and message fields for documented API failures. Official documentation.

Preserve the status, exact type, request identifier when present and the model used. The message gives useful context, but a diagnostic record should not depend on a screenshot of a transient terminal line. Store safe structured metadata and remove the authorization header and sensitive prompt material.

First determine whether a provider response arrived. A missing environment variable, package import problem or local connection error belongs to a different stage from a JSON API rejection. Keep that stage visible in the application so a configuration failure is not mislabeled as model unavailability.

Error code table

Status	Documented type	Short literal phrase	Investigation and action
401	`invalid_authentication_error`	Invalid Authentication	Match key, endpoint and header.
401	`incorrect_api_key_error`	Incorrect API key provided	Check the deployed secret value.
404	`resource_not_found_error`	Model not found	Inspect identifier, status and account access.
429	`engine_overloaded_error`	The engine is currently overloaded	Respect retry timing and reduce pressure.
429	`exceeded_current_quota_error`	Token quota is insufficient	Inspect balance and account state.
429	`rate_limit_reached_error`	Organization-level concurrency limit reached	Coordinate producers and reduce active work.
500	`server_error`	Server error	Preserve request evidence and inspect service state.

The phrases are short excerpts identifying documented cases; actual responses can contain additional detail. Read the full redacted response when deciding the action. The table is an investigation aid and does not establish the precise wording your account will receive.

Authentication errors

Confirm the key’s issuing platform and the configured API base URL together. Then inspect whether the running process received the intended secret. Recreating a key without checking either can repeat the same failure and leave unused credentials behind.

For deployed services, compare the launch environment with the interactive test. A task runner may load a different configuration file or inherit no environment variable at all. Use a presence check that does not print the value, then make the smallest authorized request from that path.

Follow the Moonshot key guide for a controlled replacement and rotation. Keep the credential’s project ownership in the same record as the deployment that consumes it.

Rate and quota errors

Use the error type to select the investigation before changing traffic or funding. Temporary service pressure should lead to a bounded wait and a check of completion deadlines. A balance condition should pause the queue for an owner action. Organization pacing should lead to coordination across the producers using that shared resource.

Record the number of attempts already made. If the client and worker both retry, one user task can generate more provider calls than the visible worker counter suggests. Pick a single retry owner, expose the final failure state and retain the task identity for a controlled restart.

Read Kimi rate-limit scopes with the actual project and organization involved. A new project should not be treated as an escape from a shared organization constraint.

Request validation errors

Reduce the payload to its model, messages and a supported minimal parameter set. Check JSON types and role ordering before adding optional tools or structured output. Restore one feature at a time, retaining a passing request after each step so the source of a validation failure remains clear.

For file-related work, verify that the file is nonempty and that its intended purpose matches the documented endpoint. Keep upload errors separate from inference errors. A successful file operation does not establish that the later model request includes the extracted content correctly.

Do not repeatedly submit unchanged invalid payloads. A short request-shape correction is more useful than a retry policy that converts a deterministic input problem into an extended incident.

Model and context errors

Check the current model list when a request selects an old route. The application may have inherited an identifier from a working example that predates a retirement. Keep model configuration centralized enough to locate, and search scheduled job definitions before declaring a migration complete.

For input-capacity problems, inspect the assembled request rather than only the last user message. History, retrieved passages, tool definitions and output allowance can all be relevant to the request shape. Preserve source selection when reducing the input: silently dropping necessary evidence can turn a visible validation error into a harder-to-detect wrong answer.

Use the model guide for current status and parameter conventions. Confirm a smaller safe fixture before retrying the full application input.

Server errors and status

For a persistent service error, keep the timestamp, safe request metadata, returned identifier and bounded retry history. Check the official status evidence linked from the provider hub. A green status page does not invalidate a specific recorded failure, and a broad incident does not prove that an unrelated request bug has been fixed.

If a stream ends early, preserve the distinction between partial output and a completed answer. Do not hand a truncated patch or document summary to downstream code as if it met the application contract. A resumed or repeated generation must be reconciled before any tool side effect is repeated.

After recovery, return traffic gradually and inspect useful completions. Clear the queued work according to task identity and deadline, not merely the order of failed attempts. This keeps an incident from producing duplicate downstream operations when service becomes available.

Use the AI API cost calculator to turn the model and workload you are considering into an estimate.

Last verified 12 Sep 2026 · Source ↗

Frequently asked questions

Why store error.type instead of only HTTP status?

It distinguishes conditions that share a status but need different corrective actions.

Should I top up after every overload message?

No. Diagnose service pressure separately from account quota.

What can make a valid-looking key fail?

A wrong issuing-platform endpoint, missing deployed environment value or malformed authorization header.

Should invalid JSON be retried unchanged?

No. Correct the request shape and verify a smaller passing payload.

Can partial streaming output count as success?

Only if the application’s explicit contract accepts that state; ordinary completed-answer handling should not assume it.

What should a support reproduction contain?

A minimal redacted request, exact model and interface, status, type, time and request identifier when available.

Sources

Last verified 12 Sep 2026 · Source ↗