Open Source LLM Projects
Discover 273 open source LLM repositories from GitHub, each with an analysis of what it does, key features, use cases and alternatives. LLM projects here are most often combined with Python, AI Agents and AI. Last updated October 4, 2026.
273 repositories · updated October 4, 2026
ai-llm-comparison: Compare AI Model Pricing and Features
A web app for comparing language models from multiple providers, with pricing estimates and side-by-side comparisons. It helps developers, businesses, and researchers narrow down model options using pricing and capability information.
unstructured: Turn Documents Into Structured Data
Unstructured is a Python library for parsing and preprocessing documents into structured elements for downstream applications, including LLM workflows. It supports many file types, with format-specific dependencies for some inputs.
LLMSanitize: Detect Contamination in NLP Data and LLMs
LLMSanitize brings together methods for checking whether NLP datasets or language models may be contaminated by training data. It is aimed at researchers and evaluators who need to assess benchmark reliability across open- and closed-data settings.
files-to-prompt: Turn Files into LLM-Ready Prompts
files-to-prompt is a Python command-line tool that gathers selected files and formats their contents into a single prompt. Use it to provide an LLM with project context without copying files together by hand.
llm-reasoners: Build and Inspect LLM Reasoning Algorithms
LLM Reasoners is a Python library for building and evaluating multi-step reasoning methods with large language models. It suits researchers and developers who need reusable search algorithms, model backends, and tools to inspect reasoning traces.
gitingest: Turn Git Repositories into LLM-Ready Text
Gitingest packages a Git repository or local directory into a structured text digest designed to provide code context to language models. Use it from the command line, Python, a browser extension, or its hosted web app.
ai-engineering-toolkit: Find Tools for Building LLM Apps
A categorized directory of libraries, frameworks, and platforms for building, evaluating, and deploying LLM applications. Use it to discover options across the AI engineering stack, then compare and verify tools before adopting them.
giskard-oss: Test and Red-Team LLM Agents
Giskard is a Python toolkit for evaluating agent behavior and probing AI systems for vulnerabilities. It suits teams building LLM agents or RAG applications that need repeatable checks, safety testing, and adversarial evaluation.
EasyEdit: Edit Knowledge and Steer Large Language Models
EasyEdit is a framework for changing specific knowledge or behavior in large language models and evaluating the effects. It brings together multiple editing and inference-time steering methods for researchers and developers comparing approaches or testing targeted edits.
cactus: Run AI Inference on Phones and Wearables
Cactus is a C++ inference engine for running language, vision, and speech models on mobile and edge devices. It combines quantization, device-focused kernels, and optional cloud handoff for applications that need local inference with a fallback for harder queries.
poml: Structure and Render Prompts for Language Models
POML is a markup language and toolkit for building structured, reusable prompts for large language models. It combines templating, data components, styling, and development tools for teams managing prompts in code.
ai-file-sorter: Organize and Rename Files with AI
AI File Sorter is a cross-platform desktop app that suggests categories and clearer filenames for images, documents, and supported media. Review every proposed change before applying it, using local models for offline, on-device workflows or remote models with your credentials.