Show HN: Getting GLM 5.2 running on my slow computer (github.com)

A developer has successfully launched the massive 744-billion parameter Mixture-of-Experts model, GLM-5.2, on a consumer-grade machine with just 25 GB of RAM using a streamlined C-based engine called colibrì. This setup uniquely allows the model to operate with zero dependencies, leveraging disk streaming for expert parameters and validating its responses against a robust architecture. The model achieves impressive load times—around 32 seconds—and maintains a manageable RAM footprint of approximately 9.9 GB for dense operations, despite its vast size. This development is significant for the AI/ML community as it democratizes access to one of the largest models available, making it possible to run advanced AI tasks on less powerful hardware. Key innovations include a highly efficient streaming mechanism that loads required parameters on demand, a specialized quantization scheme to optimize performance, and native multi-token prediction capabilities that enhance response accuracy. The entire project showcases not only the potential for running large-scale models on limited resources but also emphasizes the importance of community contributions to further refine and enhance AI capabilities.