Error 504: what to do when glm-5.2 fails

A 504 means the gateway timed out waiting for the upstream model: the request was sent, but the upstream did not return within the gateway timeout.

504 Gateway Timeout means the gateway gave up waiting for the upstream response. The request was forwarded, but no result came back within the gateway limit. Shortening the output, switching to streaming, or lowering max_tokens usually fixes it.

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: The upstream took longer than the gateway timeout allows. The recommended first action is: Switch to streaming output.

Common causes

• The upstream took longer than the gateway timeout allows
• A long context pushed inference time up
• An upstream node is stuck
• A non-streaming request with a very long output

How to fix

• Switch to streaming output
• Shorten the context and lower max_tokens
• Retry after a short wait
• Use a model with faster inference

Retry with exponential backoff

The snippet below retries when glm-5.2 returns 504, 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 429 — causes and fixes
• 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 401 — causes and fixes
• glm-5.2: error 403 — causes and fixes
• glm-5.2: error 400 — causes and fixes

Other models with the same error

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• deepseek-v4-pro
• 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

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Data updated: 2026-10-10 12:10