Deploying this model locally is quickest when done via Docker.
Simply follow the directions outlined below.
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The loader auto-caches the model archive (several GBs included).
The installer will automatically analyze your hardware and select the optimal configuration for your system.
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📎 HASH: f50806b43cf23b7c0972191d8e7df1f8 | Updated: 2026-06-23
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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) |