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[Critical] GLM-5.2 API is unusable due to severe rate limiting — 2 consecutive days of near-total outage #83

Description

@itanyplus

Title: [Critical] GLM-5.2 API is unusable due to severe rate limiting — 2 consecutive days of near-total outage

Description

GLM-5.2 API has been effectively unavailable for large portions of the past 3 days due to rate limiting. This is a production-blocking issue affecting paid users.

Timeline & Evidence

June 15 (Day 1 — near-total outage):

  • 285 × HTTP 429 errors from midnight through ~16:51 (Beijing time)
  • Failure rate: ~50% of all requests
  • 39 fallback triggers, 37 probe successes, 1 complete fallback chain exhaustion
  • Error: 429 该模型当前访问量过大,请您稍后再试
  • Service recovered around 16:51

June 17 (Day 2 — progressively worsening):

Time Window Rate Limit Errors Trend
03:00-04:00 2 Low load
08:00-09:00 4 Morning pickup
10:00-11:00 9 Rising
11:00-12:00 22 Surge — every single message fails
  • 71 total HTTP 429 errors so far today (still ongoing)
  • 18 independent message runs triggered fallback
  • 100% failure rate during the 11:00-12:00 window — all primary calls to glm-5.2 returned 429
  • Every request forced to fallback to an alternative model

Environment

  • Endpoint: zhipuai/glm-5.2 via OpenClaw Gateway (OpenAI-compatible API)
  • Account type: Paid GLM Coding Plan (via ZhipuAI API)
  • Usage pattern: Normal developer assistant workload — single-user conversations, not batch or high-concurrency
  • Standard retry/backoff: Yes, configured per API docs

Impact

  • Paid service is effectively down during work hours
  • Every user interaction requires model fallback (defeating the purpose of subscribing to GLM-5.2)
  • The problem is degrading: more errors per hour as the day progresses
  • Community reports confirm this is widespread (Reddit r/ZaiGLM: "GLM 5.2 on z.ai is getting hammered")

Request

  1. Acknowledge that this is a capacity issue, not a per-account problem
  2. Provide a timeline for capacity expansion
  3. Explain what "Fair Usage Policy" limits actually apply and how users can stay within them
  4. Compensate affected users for the unusable service days

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