Qwen3.6 27B SuperDense

--- license: apache-2.0 base_model: - Qwen/Qwen3.6-27B tags: - GGUF - Imatrix - Qwen - Dense - Qwen3.6 - LLM - Text --- # 📟 Qwen3.6-27B-Dense-Imatrix-IQ3_M.gguf (2026 Edition) > "Local intelligence... to the max." This is a custom-quantized version of **Qwen3.6-27B**, specifically optimized to obtain the highest possible local byte-intelligence ratio with 24GB+ RAM consumer laptops or computers. ## 🧠 Why this model is different Unlike a standard quant, this model was processed using a **custom Importance Matrix (imatrix)**. The training data for the imatrix was hand-curated to preserve: * **Incredible reasoning:** Inclusion of custom coding examples built with frontier models provides high retention of very specific and sharp architectural reasoning skills * **Logical Flow:** Inclusion of `llama.cpp` source code, logic puzzles, and historical writing in the imatrix training to ensure the model stays coherent at low bitrates. * **High Speed:** Built using llama.cpp specifically for local-first AI and edge computing setups like apple silicon with minimum 24GB RAM ## 🛠 Quantization Details - **Base Model:** Qwen3.6-27B - **Quantization:** IQ3_M - **Format:** GGUF - **Size:** ~12.58 GB - **Context Length:** 262144 tokens ### ⚙️ Recommended Inference Settings Optimize for balance between creativity and coherence: * **`--repeat-penalty`: 1.1 – 1.4** *(Sweet spot! Pushes away from familiar loops. >1.5 causes "robot-speak".)* * **`--repeat-last-n`: 128 – 256** *(Larger window ensures the model doesn't forget recent repetitions.)* * **`--temperature`: 0.7 – 0.8** *(Prevents over-committing to safe/repetitive tokens.)* * **`--top-p`: 0.90** *(Trims low-probability hallucinations without killing creativity.)* * **`--min-p`: 0.05 – 0.1** *(Optional: Prunes very low-probability tokens if your backend supports it.)* ### 📈 Perplexity Benchmarks The following results were generated using `llama-perplexity` on the `wikitext-2-raw/wiki.test.raw` dataset. | Model | Precision | Perplexity (PPL) | Δ PPL | | :--- | :--- | :--- | :--- | | Qwen3.6-27B- (no-imatrix) | IQ3_M | **7.4952** | - | | **Qwen3.6-27B- (Imatrix)** | **IQ3_M** | **7.1485** | **-0.3467** | ### ⚖️ Evaluation Verdict Refined Accuracy: A PPL reduction of -0.3467 indicates that the I-Matrix successfully "pinned" the critical weights for the Gated DeltaNet layers, further smoothing out the IQ3_M ex...

Source context: 125 downloads · 4 likes · Repo macwhisperer/Qwen3.6-27B-SuperDense

Source context: 490 downloads · 3 likes · Repo macwhisperer/Qwen3.6-27B-SuperDense