Qwen3.6 27B — Claude Opus Reasoning Distilled · GGUF GGUF quantized versions of rico03/Qwen3.6 27B Claude Opus Reasoning Distilled for use with llama.cpp, Ollama, LM Studio, and any GGUF compatible runtime . 🙏 This model was trained following the methodology by Jackrong, adapted for Qwen3.6 27B. 🎯 What Is This? Qwen3.6 27B fine tuned on ~14k Claude 4.6 Opus reasoning traces. The model adopts a structured, efficient thinking style — concise on simple tasks, deep on hard ones — while fully preserving the base model's exceptional coding and math capabilities. Key improvement over base Qwen3.6 27B: reduced verbose reasoning loops, replaced with Claude style structured step by step decomposition. Base model benchmark: 📦 Available Quantizations Choose based on your available VRAM/RAM: File Size Min VRAM Quality Recommended For Q2 K ~10GB 12GB ⭐⭐ Very limited hardware Q3 K M ~13GB 16GB ⭐⭐⭐ Budget setups Q4 K S ~16GB 20GB ⭐⭐⭐⭐ Good balance Q4 K M 16.5GB 20GB ⭐⭐⭐⭐ ✅ Best choice Most users Q5 K S ~19GB 24GB ⭐⭐⭐⭐⭐ High quality Q5 K M ~20GB 24GB ⭐⭐⭐⭐⭐ High quality Q6 K ~23GB 28GB ⭐⭐⭐⭐⭐ Near lossless Q8 0 28.6GB 36GB ⭐⭐⭐⭐⭐ Maximum quality Q4 K M is recommended for most users — best quality t…
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