๐Ÿ“Ÿ Qwen3.5-4B-Dense-Imatrix-Q4_K_M.gguf (2026 Edition)

"Local intelligence... to the max."

This is a custom-quantized version of Qwen3.5-4B, specifically optimized to obtain the highest possible local byte-intelligence ratio with 8GB+ RAM consumer laptops or computers.

๐Ÿง  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

๐Ÿ›  Quantization Details

  • Base Model: Qwen3.5-4B
  • Quantization: Q4_K_M
  • Format: GGUF
  • Size: ~2.71 GB
  • Context Length: 262144 tokens

๐Ÿ“ˆ Perplexity Benchmarks

The following results were generated using llama-perplexity on the wikitext-2-raw/wiki.test.raw dataset.

Model Precision Perplexity (PPL) ฮ” PPL
Qwen3.5-4B (Baseline) BF16 9.9450 -
Qwen3.5-4B (Quant) Q4_K_M 10.0558 +0.1108

โš–๏ธ Evaluation Verdict

coming soon

๐Ÿš€ Hardware Performance (Apple M2)

coming soon

๐ŸŒ Links

Check out my other models!

24GB+ (RAM)

Qwen3.6-35B-SuperMoE.

Qwen3.6-27B-SuperDense.

Gemma4-31B-SuperDense.


8GB+ (RAM)

Qwen3.5-9B-SuperDense.

Gemma4-4B-SuperDense.

Gemma4-2B-SuperDense.


4GB+ (RAM)

Smartchild.


All make excellent companions to this model!


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