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Qwen 3.6 27B model struggles with agentic tasks, user reports

A user on Reddit's r/LocalLLaMA forum has reported significant issues with the Qwen 3.6 27B model when performing agentic tasks. While the model excels at generating impressive single prompts and longer content compared to its predecessors, it consistently fails in multi-turn, agentic work. The user experienced continuous errors and a lack of adherence to directions, with the model making "braindead" mistakes approximately every four turns. This led the user to revert to the older Qwen 3.5 122B model for their agentic workflows. AI

IMPACT Highlights potential limitations in current models for complex, multi-turn AI agent applications.

RANK_REASON User report on a specific model's performance limitations, not a formal release or benchmark.

Read on r/LocalLLaMA →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Qwen 3.6 27B model struggles with agentic tasks, user reports

COVERAGE [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/TokenRingAI ·

    Qwen 3.6 27B absolutely fails at agentic work

    <!-- SC_OFF --><div class="md"><p>I have been running Qwen 3.5 122B at 4 bit for quite a while, and have started running it at 5 bit recently now that Llama.cpp has comparable performance to VLLM.</p> <p>I have also tried, several times, to use Qwen 3.6 27B at 8 bit &amp; 16 bit,…