Reasoning-v1-20m Reasoning Dataset

Reasoning-v1-20m is a large-scale reasoning dataset released by Glaiveai in 2025, containing about 20 million reasoning traces, covering complex problems in multiple fields such as mathematics, programming, science, etc. This dataset aims to help the model learn complex reasoning logic and improve its performance in multi-step reasoning tasks by providing rich examples of the reasoning process.

The Reasoning-v1-20m dataset is characterized by its huge data volume and diverse reasoning tasks. It not only covers a wide range of fields, but also provides a detailed chain of thought (COT) for each question, helping the model understand the step-by-step reasoning process from question to answer. This structured data form provides rich material for model training, enabling it to learn and optimize reasoning strategies.

This dataset is widely used in the fields of natural language processing and artificial intelligence, especially in training and optimizing reasoning models. It can help models show higher accuracy and logic when dealing with complex problems, such as in solving mathematical problems, solving programming problems, and reasoning about scientific problems. In addition, this dataset can also be used to study the effectiveness of different reasoning strategies and promote the advancement of natural language processing technology in reasoning tasks.