Qwen3.6-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking-NEO-CODE-Di-IMatrix-MAX-GGUF Offline on PC Full Speed NPU Mode

Qwen3.6-40B-Claude-4.6-Opus-Deckard-Heretic-Uncensored-Thinking-NEO-CODE-Di-IMatrix-MAX-GGUF Offline on PC Full Speed NPU Mode

If you want the fastest local installation for this model, use Docker.

Refer to the instructions below to proceed.

The setup auto-downloads all needed files (several GBs).

The automated installation script takes care of everything by tailoring the setup perfectly to your system specs.

🧾 Hash-sum — bf1fd4d29c6cdd19c1bfc36e39d182b8 • 🗓 Updated on: 2026-06-25
  • Processor: next-gen chip for heavy context processing
  • RAM: minimum 16 GB for stable 8B model loading
  • Disk Space: at least 100 GB for multiple local LLM variants
  • 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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