The fastest tactical way to launch this model locally is via a Docker image.
Review and follow the instructions below.
The setup auto-downloads all needed files (several GBs).
The installer will automatically analyze your hardware and select the optimal configuration.
🔗 SHA sum: c390b7dbd9f3c8dd44bb19da9c4af414 | Updated: 2026-07-06
- Processor: Intel i7 / Ryzen 7 for heavy Quantized models
- RAM: 32 GB highly recommended for 26B+ GGUF models
- Disk Space: required: fast PCIe 4.0 drive for instant boots
- Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration
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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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