The release of open source reasoning models as the next generation of LLMs represents a significant leap forward in how machines approach complex problem-solving tasks. These models introduce new architectures, design decisions, and training methodologies and demonstrate remarkable capabilities in tackling reasoning challenges while maintaining computational efficiency. The democratization of such advanced AI capabilities through open source initiatives has accelerated progress in the field, enabling researchers and developers worldwide to build upon existing frameworks. Moreover, with new advances, new avenues for research become available to researchers, even in low-compute resource settings.