Error 429: what to do when kimi-k2.5 fails

A 429 means you hit a rate limit: the number of requests or tokens sent within a time window exceeded your plan quota.

429 Too Many Requests is a rate-limit response, not an error. It means the request itself is valid but exceeded the request rate or concurrency allowed by your current plan. Back off and retry within the window indicated by the response headers; the request body does not need to change.

kimi-k2.5 is served by Moonshot AI. Everything on this page — triggers, fixes and measured data — is compiled from the real runtime behaviour of this model at the gateway layer.

At this gateway, the most common trigger is: Too many concurrent requests. The recommended first action is: Limit concurrency and retry with exponential backoff.

Common causes

  • Too many concurrent requests
  • Quota of the current plan exhausted
  • Retrying immediately without backoff

How to fix

  • Limit concurrency and retry with exponential backoff
  • Switch to a plan with a larger quota
  • Cache repeated requests

Retry with exponential backoff

The snippet below retries when kimi-k2.5 returns 429, up to 5 attempts, with an increasing wait plus random jitter so concurrent calls do not retry in lockstep. Read the base URL and API key from environment variables — never hardcode them.

import os, time, random
import requests

BASE  = os.getenv("OPENAI_BASE_URL")   # e.g. https://<your-gateway>/v1
KEY   = os.getenv("OPENAI_API_KEY")
MODEL = 'kimi-k2.5'


def chat(messages, retries=5):
    """Retry with exponential backoff + jitter."""
    for i in range(retries):
        try:
            r = requests.post(
                BASE + "/chat/completions",
                headers={"Authorization": "Bearer " + KEY},
                json={"model": MODEL, "messages": messages, "stream": True},
                timeout=60,
            )
            if r.status_code == 429 or r.status_code >= 500:
                time.sleep(min(2 ** i + random.uniform(0, 1), 30))
                continue
            r.raise_for_status()
            return r.json()
        except requests.exceptions.Timeout:
            time.sleep(min(2 ** i + random.uniform(0, 1), 30))
    raise RuntimeError("gave up after " + str(retries) + " retries")


print(chat([{"role": "user", "content": "hello"}]))

Key facts for this model

API endpointhttps://api.airai.cc/v1
OpenAI-compatibleOpenAI-compatible
VendorMoonshot AI
Context262.1K
CapabilitiesReasoning, Tools, Open Weights, Vision
API formatsopenai, openai-response, openai-response-compact, anthropic, gemini, openai-alpha-search
Cache discount0.556×

FAQ

Is 429 more likely in multi-turn conversations with kimi-k2.5?

This is a client-side configuration issue; nothing changes server-side. The 262.1K context window sets the maximum input per request; anything beyond it is rejected outright. Fail fast on parameter errors instead of spending retries on them. Truncate or summarise long inputs — it noticeably reduces 429.

How long should the timeout be?

Concurrency and timeouts are the real variables here, not the model itself. This model has a 262.1K context window and comes from Moonshot AI. Add a cache layer so repeated requests do not all hit the model.

Is 429 related to how kimi-k2.5 is billed?

Only the output already produced is billed; the failed part is not. Input price is about $0.41 per million tokens. Check your balance and rate limits in the console before debugging code. When estimating cost from , include the retry budget.

Can 429 cause data loss?

It is usually transient and recovers on its own. The capability tags for this model are Reasoning, Tools, Open Weights, Vision. If it persists for several minutes, contact platform support to confirm upstream status.

Other errors on this model

Other models with the same error

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Data updated: 2026-10-11 19:15

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