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.