Local AI execution: challenges and setup requirements

Running artificial intelligence models locally on personal hardware offers increased data privacy and security by keeping information off the cloud. However, users face significant technical hurdles to achieve performance comparable to hosted services.

To run open models on laptops, specific hardware is required. For small models, at least 8 GB of video memory or an Apple Silicon Mac is recommended, while professional use typically requires 24 GB of video memory or more. Software tools like Ollama, which is command-line based and geared toward developers, and LM Studio, which provides a graphical interface, are the primary options for local execution.

Testing reveals that local software often fails to perform basic tasks, such as summarizing documents, when using default settings. Many free utilities limit the memory allocated to text reading, causing them to truncate files and only process the final pages. To function correctly, users must manually adjust settings to expand the text context window, force RAM compression, and configure hardware acceleration, such as Metal for Mac or Vulkan for Windows.