Claude Opus Reasoning Traces for Mathematical and Logical Tasks

A synthetic dataset of 10,000 reasoning traces generated by the Claude Opus 4.6 model, designed for Supervised Fine-Tuning and Distillation. It captures the model's internal 'Chain of Thought' with a focus on mathematical accuracy and structured logical deduction.

Use Cases

• Supervised Fine-Tuning of smaller models to inherit the sophisticated reasoning patterns of Claude Opus 4.6.
• Distillation of high-fidelity 'Chain of Thought' reasoning traces for mathematical tasks.
• Training models on structured logical deduction sequences for improved accuracy.

Strengths

• Contains 10,000 high-fidelity reasoning traces.
• Focuses on high-difficulty mathematical and logical reasoning.
• Synthesized specifically for model training and distillation.

Limitations

• Synthetic data may not fully represent real-world reasoning patterns.
• Limited information on data diversity or potential biases in the generation process.
• Unknown file formats and structure may complicate initial use.

Provenance

Source

Hugging Face, author alibayram.

Collection Method

Synthesized using Claude Opus 4.6 model.

Freshness

Last updated 2026-03-16.