GLM-5.2-Conversation: 50,000 Traces Distilled from a High-Reasoning Model

50,000 conversation traces distilled from the GLM-5.2 language model on high-reasoning tasks. The dataset contains 120 million tokens across speaking domains like greetings and customer support, as well as STEM and programming topics. It was created by author 'ianncity' and last updated on Hugging Face in July 2026.

Use Cases

• Training or fine-tuning conversational AI models based on the described high-reasoning traces.
• Analyzing model outputs for logical reasoning patterns based on the 'Logical Questions' domain mentioned.
• Studying the structure of step-by-step explanations generated by language models.
• Benchmarking creative writing or motivational language generation from AI models.

Strengths

• Contains 50,000 individual conversation traces.
• Comprises 120 million tokens of text data.
• Covers a diverse range of topics including STEM, programming, and multiple speaking domains as listed.

Limitations

• Description metadata is limited; actual data quality requires manual inspection after download.
• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.

Provenance

Source

huggingface

Collection Method

Distilled from the GLM-5.2 language model on high-reasoning tasks.

Freshness

Last updated 2026-07-13 11:07:53; freshness should be verified.