Show HN: Llmfit;94 models, 30 providers.1 tool to see what runs on your hardware (github.com)

A new terminal tool, **llmfit**, has been released, designed to optimize the deployment of large language models (LLMs) based on a user's specific hardware capabilities. It evaluates 94 models from 30 providers, scoring them across quality, speed, fit, and context to inform users about which models can run effectively on their systems. The tool features an interactive terminal user interface (TUI) and classic command-line interface (CLI) modes, making it accessible for both casual users and developers. It supports various hardware configurations, including multi-GPU setups and dynamic quantization, and provides personalized recommendations to maximize performance. This release is significant for the AI/ML community as it bridges the gap between model availability and real-world computing constraints, enabling developers and researchers to make informed choices about deploying LLMs in their environments. The scoring system combines multiple metrics, allowing for nuanced fit analysis that adapts to each user’s hardware while supporting modern architectures like Mixture-of-Experts (MoE). As AI continues to proliferate across platforms, tools like llmfit will be essential for optimizing performance and resource utilization, ultimately enhancing the efficiency of AI model deployment.