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  "path": "/t/stealth-model-swap-gpt-5-5-high-claims-knowledge-cutoff-is-june-2024/1381918#post_5",
  "publishedAt": "2026-05-28T07:24:56.000Z",
  "site": "https://community.openai.com",
  "textContent": "First of all, I have tremendous respect for your deep insight into LLM architectures  . It’s clear from your words that you have a profound understanding of how these underlying token factories operate. I’d like to use my limited knowledge to piece together your explanation and see if I’m understanding it correctly:\n\n  1. When the model tells me its training cutoff is June 2024, you believe this is a hallucination.\n\n  2. In a completely isolated session where I banned internet browsing, it stated the latest OpenAI model it knows of is GPT-4o (released in May 2024). You believe this is also a hallucination.\n\n\n\n\nSo, the model hallucinated the exact same historical timeline and identical year/month constraints across two completely independent tests. In your view, this is just a highly precise coincidence, correct?\n\nI completely agree with your point that LLMs lack a native self-awareness of the hardware or specific clusters they run on. However, as developers, we both know that Codex and most production-level Agent workflows inject metadata via system prompts into the session context to define the environment.\n\nWhen I poked further into the session metadata, Codex explicitly spat out that its current environment is **“Codex based on GPT-5.0”** —whose actual training data timeline happens to align closely with mid-2024.\n\nAre we still calling this a triple-hallucination-coincidence?\n\nTo me, this no longer looks like a token factory spinning wild fantasies. It looks like a classic backend misconfiguration where the routing layer is pulling from a legacy GPT-5.0 container or an old Codex base, even though the frontend UI proudly displays “GPT-5.5 High.”",
  "title": "Stealth Model Swap? GPT-5.5 High Claims Knowledge Cutoff is June 2024"
}