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  "path": "/t/chatgpt-pedantacy-problems/1382101#post_1",
  "publishedAt": "2026-05-30T20:28:11.000Z",
  "site": "https://community.openai.com",
  "textContent": "I don’t know if its just me, but ChatGPT is overly pedantic.\n\nPrompt:\n\nQwen 3 models under 4B are notouriously unstable, right now Qwen 3.5 0.8B said The user sent a lot of text that starts with and then continued to repeat the exact thing I said, every single charachter\n\nChatGPT Response:\n\nThat result is interesting, but I’d be careful about jumping from:\n\n> “This small model behaved strangely under pathological input”\n\nto:\n\n> “Qwen under 4B is notoriously unstable.”\n\nA few reasons:\n\n  * **0.8B parameters is extremely small by modern standards.** Small models generally have much less capacity for long-context robustness, compression, instruction retention, and recovery.\n\n  * **Echoing / copying user text** is a common failure mode in small models under repetitive or overloaded contexts.\n\n  * If it literally started saying things like _“The user sent a lot of text that starts with…”_ and then copied the pattern, that sounds more like **meta-pattern completion** or **context summarization failure** than a unique architecture-specific bug.\n\n\n\n\nWhat you described actually gives you a potentially useful distinction:\n\n**Gemini Flash behavior:**\n→ repetitive degradation / weird continuations / recovery\n\n**Small Qwen behavior:**\n→ meta-commentary + copying behavior\n\nThose are different failure signatures.\n\nAlso, one correction: you mentioned “Qwen 3.5 0.8B.” Are you referring to a specific Qwen 3 0.8B release, or did you mean a Qwen 2.5 / Qwen 3 variant? Because the exact checkpoint matters if you’re comparing architectures.\n\nFrom a research perspective, I’d be more surprised if a **0.8B model survived hundreds of thousands of repetitive tokens gracefully** than if it failed.\n\nIt took what I said and framed it in a way where it implies that I am wrong.",
  "title": "ChatGPT Pedantacy Problems"
}