On April 30th, someone on LocalLLaMA posted something quiet and specific: Qwen 3.6 loops. Not in a catastrophic, model-is-broken way. In the more insidious way — output that keeps arriving, syntactically coherent, contextually plausible, while delivering nothing new. Phrases recycle. Sentence structures return wearing slightly different clothes. The token stream doesn't stop; it just stops going anywhere. A score of 4.3 is its own kind of signal — high enough that people recognised the pattern and engaged with it, low enough that nobody called it a crisis. That gap between personal frustration and community alarm is exactly where subtle, reproducible bugs tend to live longest. Nobody files a formal report. Nobody opens a GitHub issue with enough detail to drive a fix. The problem just circulates quietly, surfacing in user sessions, degrading outputs that look fine until you read them twice.
If confirmed, here is what this means. Looping and repetition in a model of Qwen 3.6's capability tier isn't a minor annoyance — it's a reliability tax on every application built on top of it. Developers running long-form generation, agentic pipelines, or document summarisation workflows would be paying that tax on every run, often without knowing it. The outputs pass a surface-level sanity check and fail a deeper one, which is precisely the failure mode that escapes automated testing. Downstream products built on Qwen 3.6 could be quietly degrading user trust right now while their dashboards show nothing unusual. For Alibaba's standing in the open-weights community, sustained repetition bugs also carry reputational weight — not because they're unforgivable, but because how quickly and transparently they're addressed tells you everything about how seriously a lab takes the deployment experience, not just the benchmark score.
Watch for follow-up threads on LocalLLaMA or Hugging Face with reproducible examples and specific prompts that trigger the loop — that kind of evidence would force a formal response from the Qwen team. Equally telling would be silence: if this disappears without acknowledgement, it will resurface in someone else's frustrated post three months from now.
<!-- SC_OFF --><div class="md"><blockquote> <p>Wait, I need to be careful about the "no_think" tag in the system prompt. The system prompt says <code>/no_think</code>.
<!-- SC_OFF --><div class="md"><p>In LM Studio the new Qwen 3.5 models (4b 9b 27b 122b) when analyzing large (more than 50k tokens) texts start to output gibberish. It is not a
<!-- SC_OFF --><div class="md"><p>Just swapped Qwen 3.5 for the 3.6 variant (FP8, RTX 6000 Pro) using the same recommended generation settings. My stack is vLLM (v0.19.0) + Open
<!-- SC_OFF --><div class="md"><p>Hey all, </p> <p>im having a crisis that i just cant figure... </p> <p>i used Qwen3.6-27B-GGUF:UD-Q8_K_XL ever since it came out (on a DGX SPARK)
<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s1bjtr/getting_stuck_in_loops_w_tool_calls/"> <img alt="Getting Stuck in Loops w Tool Calls"
<!-- SC_OFF --><div class="md"><p>I am testing out some loop identification, protection & recovery features in our agent, and I am looking for a model that gets stuck in loops
<!-- SC_OFF --><div class="md"><p>So in response to the Great Token Reconning of 2026, I decided to try out Qwen 3.6 as a daily driver, and although it's only been about a day, I
<table> <tr><td> <a href="https://www.reddit.com/r/singularity/comments/1s7rcwr/qwen35_omni_qwens_latest_generation_of_fully/"> <img alt="Qwen3.5 Omni - Qwen’s latest generation
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