Error 429: what to do when glm-5.2 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.

glm-5.2 is served by Z.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 glm-5.2 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 = 'glm-5.2'


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

FAQ

Other errors on this model

• glm-5.2: error timeout — causes and fixes
• glm-5.2: error 500 — causes and fixes
• glm-5.2: error 502 — causes and fixes
• glm-5.2: error 503 — causes and fixes
• glm-5.2: error 504 — causes and fixes
• glm-5.2: error 401 — causes and fixes
• glm-5.2: error 403 — causes and fixes
• glm-5.2: error 400 — causes and fixes

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• glm-5
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• kimi-k3
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• mimo-v2.5
• gpt-4o
• claude-opus-4-6

Back to the model page

Data updated: 2026-10-10 12:10