GitHub - AlexsJones/llmfit: Hundreds of models & providers. One command to find what runs on your hardware.
Hacker News
March 1, 2026
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GitHub - AlexsJones/llmfit: Hundreds of models & providers. One command to find what runs on your hardware. A terminal tool that right-sizes LLM models to your system's RAM, CPU, and GPU. Detects your hardware, scores each model across quality, speed, fit, and context dimensions, and tells you which ones will actually run well on your machine.
llmfit is a powerful tool designed for users looking to optimize their use of large language models (LLMs) by matching the best-performing models with their specific hardware setups. The tool offers an interactive terminal user interface (TUI) as its default mode, displaying system specifications and model rankings based on a composite score that considers factors like performance, memory usage, and compatibility. Additionally, it supports command-line interface (CLI) mode for those preferring traditional table-based output.
The tool's functionality extends to hardware optimization by detecting available resources such as CPU, RAM, GPU VRAM, and backend configurations. It provides detailed insights into each model's estimated speed, optimal quantization method, memory footprint, and context window, enabling users to make informed decisions about which models to deploy. llmfit also supports advanced features like multi-GPU setups, MoE architectures, dynamic quantization selection, and local runtime providers such as Ollama, llama.cpp, and MLX.
For tech enthusiasts and developers, llmfit fills a critical gap by simplifying the process of selecting and managing LLM models. It eliminates the guesswork involved in determining which models can run efficiently on personal or business hardware, thereby optimizing resource utilization and enhancing productivity. The tool's ability to provide detailed hardware requirements for each model also aids in planning upgrades or identifying compatible configurations.
By streamlining the selection and deployment process of LLMs, llmfit empowers users to maximize their computational resources while minimizing waste. This is particularly valuable for professionals working with limited hardware budgets, as it ensures they can still leverage state-of-the-art models without overextending their systems. The tool's integration with various runtime providers further enhances its utility by offering flexibility in how models are hosted and executed.
In a world where LLM adoption is rapidly increasing, tools like llmfit play a crucial role in making these technologies accessible to a broader audience. By simplifying the complexities of model management, it democratizes access to powerful AI capabilities,
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Originally published on Hacker News on 3/1/2026