
A standalone PowerShell module provides the fastest route to local installation.
Just follow the guidelines provided below.
The script takes care of fetching the multi-gigabyte model weights.
There is no manual tuning required; the builder deploys the best matching configuration.
🔧 Digest: f87caf370019c8d5d5ca85cf45df19ec • 🕒 Updated: 2026-06-30
- Processor: Intel i5 or AMD Ryzen 5 for basic 7B models
- RAM: 64 GB to avoid OOM crashes on large contexts
- Disk Space: free: 80 GB on system drive for scratch space
- GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats
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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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