Model Card: Qwen3.5-Qwen3.6-plus-Reasoning-Distilled-GGUF
Overview
This model is a distilled reasoning-enhanced variant of Qwen3.5-2B, designed to improve:
- Structured reasoning
- Step-by-step problem solving
- Decision stability
- Output efficiency (token usage)
The model is trained via distillation from a stronger reasoning model (Qwen3.6-plus), transferring:
- Clean reasoning trajectories
- Better stopping behavior
- Reduced reasoning noise
Key Improvements Over Base Model
Reasoning Efficiency
Compared to the base model, this model:
- Produces shorter and more relevant reasoning chains
- Avoids repetitive self-verification loops
- Maintains high signal-to-noise ratio
Stability
The base model often exhibits:
- Overthinking
- Infinite or near-infinite reasoning loops
- Hypothesis explosion
This distilled model:
- Converges faster to a solution
- Maintains deterministic reasoning paths
- Avoids reasoning drift
Decision-Making
- Improved reasoning termination policy
- Clearer final answers
- Better alignment between reasoning and output
Known Failure Modes
- Occasional hallucinated justifications
- Overconfidence in incorrect options
- Missing rare edge-case interpretations
- Limited deep domain reasoning beyond training distribution
Available Model files:
qwen3.6-plus-Distilled-GGUF.F16.gguf qwen3.6-plus-Distilled-GGUF.Q8.gguf
An Ollama Modelfile is included for easy deployment.