Qwen3.6-Plus Multi-Domain Reasoning Dataset for Distillation

876,205 tokens of multi-domain text data were prepared by author khazarai for knowledge distillation using the Qwen3.6-plus model. The dataset covers topics including coding, mathematics, finance, medicine, and economics. It was last updated in April 2026.

Use Cases

• Distill reasoning capabilities from the Qwen3.6-plus teacher model using the 876,205 token corpus for text generation tasks.
• Fine-tune language models on specific domains like coding or mathematics using the categorized text sequences.
• Benchmark model performance on reasoning tasks across finance, medicine, and economics domains present in the data.
• Train student models to generate long-form content by leveraging examples with a maximum sequence length of 6,500 tokens.

Strengths

• Corpus contains 876,205 tokens for distillation training.
• Data spans five distinct high-reasoning domains: coding, mathematics, finance, medicine, and economics.
• Maximum sequence length of 6,500 tokens supports training for long-context generation.

Limitations

• Specific row count, column structure, and sample data are unknown, limiting reproducibility.
• Dataset scope is defined by the single teacher model's outputs, potentially introducing model-specific biases.

Provenance

Source

huggingface

Collection Method

Prepared for distillation using outputs from the Qwen3.6-plus teacher model.

Time Range

null

Freshness

Last updated in April 2026.

Geography

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