Error 429: what to do when kimi-k2.7-code 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-k2.7-code 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-k2.7-code 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-k2.7-code'


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, Files, Open Weights, Vision
API formatsopenai, openai-response, openai-response-compact, anthropic, gemini, openai-alpha-search
Billing formulap * 0.95 + cr * 0.19 + c * 4

FAQ

How many retry attempts is reasonable?

You usually do not need to change business code, just the call cadence. Retrying is the most effective first step. With billing p * 0.95 + cr * 0.19 + c * 4, failed requests are not counted toward usage. Set the retry ceiling to 3–5 attempts and add jitter.

How can I prevent 429 on kimi-k2.7-code in advance?

Keep a fallback model ready as well. Building a fallback into the architecture is more reliable than patching errors one by one. This model from Moonshot AI has several upstream nodes the gateway can switch between. Put the model name in config, so switching upstreams needs no code change.

Do failed requests count against my rate limit quota?

Only the output already produced is billed; the failed part is not. Input price is about $0.95 per million tokens. With billing p * 0.95 + cr * 0.19 + c * 4, failed requests are not counted toward usage. Check your balance and rate limits in the console before debugging code. When estimating cost from p * 0.95 + cr * 0.19 + c * 4, include the retry budget.

When kimi-k2.7-code returns 429, is the gateway or the upstream more likely at fault?

This error is unrelated to model capability; it is a gateway-layer issue. It is usually transient and recovers on its own. The capability tags for this model are Reasoning, Tools, Files, Open Weights, Vision. If it persists for several minutes, contact platform support to confirm upstream status. Decide account-level versus model-level first; the two need completely different handling.

Other errors on this model

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Data updated: 2026-10-10 18:30

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