Error 401: what to do when glm-5.3 fails

A 401 means authentication failed: the request carries no API key, or the key is invalid, deleted or expired.

401 Unauthorized means the request carries no valid credential. The gateway could not identify the caller, so the request never reaches the upstream model. Checking the Authorization header and the key status is the only path forward.

glm-5.3 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: The Authorization header is missing. The recommended first action is: Send the header as Authorization: Bearer followed by your key.

Common causes

• The Authorization header is missing
• The key is misspelled or has stray whitespace
• The key was deleted or disabled on the Tokens page
• A key from another platform was used by mistake

How to fix

• Send the header as Authorization: Bearer followed by your key
• Generate a fresh key on the Tokens page
• Check that you are not using a key from another service
• Verify the key with a minimal curl request

Retry with exponential backoff

The snippet below retries when glm-5.3 returns 401, 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-5.3'


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-5.3: error 429 — causes and fixes
• glm-5.3: error timeout — causes and fixes
• glm-5.3: error 500 — causes and fixes
• glm-5.3: error 502 — causes and fixes
• glm-5.3: error 503 — causes and fixes
• glm-5.3: error 504 — causes and fixes
• glm-5.3: error 403 — causes and fixes
• glm-5.3: error 400 — causes and fixes

Other models with the same error

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• grok-4.3
• llama-3.3-70b-instruct
• qvq-max
• qwq-32b
• glm-5
• MiniMax-M3
• kimi-k3
• hy3
• doubao-seed-evolving
• mimo-v2.5
• gpt-4o
• claude-opus-4-6

Back to the model page

Data updated: 2026-10-10 15:45