Show HN: A GPU/VRAM filter for finding LLMs that will run on your hardware (www.whichllmmodel.com)

A new tool called Local Model Finder has been launched to help users identify which open-source large language models (LLMs) can run on their specific hardware configurations. By inputting their system's GPU and VRAM specifications, users can receive tailored recommendations on models that fit their memory capacities. This utility is particularly useful for those looking to maximize the performance of local AI applications without overextending their hardware capabilities. Key models highlighted include Mistral 3 14B, Gemma 4 12B, and Llama-3.1 8B, all of which utilize offloading techniques to optimize performance at lower memory requirements. This development is significant for the AI/ML community as it democratizes access to advanced AI models, allowing individuals and smaller organizations to experiment with and deploy LLMs without the need for high-end hardware. It emphasizes the growing trend of local model deployment, enabling users to leverage advanced AI capabilities while maintaining control over their data. The compatibility with local quantization not only improves efficiency but also broadens the scope for developers and researchers to innovate within the constraints of available resources.