local-llm is a development framework that enables developers to run large language models locally within Google Cloud Workstations or standard environments without requiring GPU hardware. It focuses on making generative AI development more accessible by leveraging quantized models and CPU-based execution, eliminating the dependency on expensive GPU infrastructure. The repository includes tools, Docker configurations, and command-line utilities that simplify the process of downloading, running, and interacting with language models directly on local or cloud-based workstations. This approach improves data privacy and control, as all inference can be performed locally without sending sensitive information to external APIs. It also integrates seamlessly with Google Cloud services, allowing developers to build and test AI-powered applications within the broader cloud ecosystem.

Features

  • Run large language models locally without GPUs
  • Support for quantized models from external repositories
  • Integration with Google Cloud Workstations environments
  • Command-line tools for model execution and interaction
  • Docker-based setup for reproducible environments
  • Improved data privacy through local inference

Project Samples

Project Activity

See All Activity >

License

Apache License V2.0

Follow local-llm

local-llm Web Site

Other Useful Business Software
MongoDB Atlas runs apps anywhere Icon
MongoDB Atlas runs apps anywhere

Deploy in 115+ regions with the modern database for every enterprise.

MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
Start Free
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of local-llm!

Additional Project Details

Programming Language

Python

Related Categories

Python Large Language Models (LLM)

Registered

2026-03-17