Quick Run Qwen3.6-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking-NEO-CODE-Di-IMatrix-MAX-GGUF

For the fastest local setup of this model, Docker is the best choice.

Follow the step-by-step instructions below.

The installer automatically pulls the model (could be multiple GBs).

The setup file includes an intelligent feature that instantly optimizes all configurations for your hardware profile.

🗂 Hash: b760eb4694fc2b7a53d5ed712c80c435 • Last Updated: 2026-06-22 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: 32 GB or higher for smooth 32k context lengths Disk Space: free: 80 GB on system drive for scratch space Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration

The model Qwen3.6-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking-NEO-CODE-Di-IMatrix-MAX-GGUF is a massive 40‑billion parameter language model designed for high‑performance inference. It leverages an advanced Transformer‑based architecture with multi‑head attention and a novel Di‑IMatrix optimization layer that dramatically reduces memory footprint while preserving accuracy. The model has been trained on a diverse, web‑scale corpus, enabling it to generate coherent, context‑aware responses across technical, creative, and conversational domains. Benchmarks show that it outperforms many existing open‑source models in reasoning, coding, and language understanding tasks, thanks to its Opus‑Deckard fine‑tuning pipeline. Its uncensored thinking mode encourages transparent reasoning steps, making it especially valuable for research and educational applications.

Specification	Value
Parameters	40 B
Context Length	8 K tokens
Training Data	≈1.5 trillion tokens
Inference Speed	≈200 tokens/s (GPU)
Quantization	GGUF (Q4_K_M)

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