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
simpleaichat: Build Python ChatGPT Apps with Minimal Code
simpleaichat is a Python library for building chat applications and workflows with OpenAI chat models. It offers conversation management, streaming, asynchronous calls, structured data, and custom tools through a compact interface.
llm-compressor: Compress Models for vLLM Inference
LLM Compressor applies post-training quantization and related model transformations to prepare Hugging Face models for vLLM deployment. It suits teams seeking smaller or more inference-efficient checkpoints, with support for multiple formats and large-model workflows.
LightLLM: Serve Large Language Models with a Python Framework
LightLLM is a Python framework for LLM inference and serving, designed for scalable deployment and fast generation. It suits teams operating model-serving systems and researchers building on inference components.
torchchat: Run PyTorch LLMs on Desktop, Server, and Mobile
torchchat is a PyTorch codebase for running and interacting with language models locally through Python, native C++ runners, and mobile apps. It supports several execution and export paths, but is no longer under active development.
TensorRT-LLM: Optimize LLM Inference on NVIDIA GPUs
TensorRT-LLM is a Python framework and runtime for efficient LLM and visual-generation inference on NVIDIA GPUs. It suits teams deploying models on NVIDIA hardware that need optimized kernels and configurable single- or distributed-GPU execution.
DataDreamer: Generate Synthetic Data and Train LLMs
DataDreamer is a Python library for building LLM workflows, generating synthetic datasets, and training or aligning models. It suits researchers and developers who want reproducible, resumable workflows across open-source and API-based models.
EasyInstruct: Generate, Select, and Prompt LLM Instructions
EasyInstruct is a Python framework for preparing instruction data and prompts for large language model research. It combines instruction generation and dataset selection tools with prompt and local-model execution modules.
OpenWebAgent: Build Web Agents for Large Language Models
OpenWebAgent is a toolkit for building web agents that automate interactions with webpages using language or multimodal models. It pairs a Chrome extension with a configurable server, aimed at developers integrating their own models.
LazyLLM: Build Multi-Agent LLM Applications
LazyLLM is a Python framework for assembling, testing, and deploying multi-agent LLM applications with low-code workflows. It suits developers who want to combine models, tools, and RAG components while iterating across local or online services.
ChatArena: Build Multi-Agent Language Game Environments
ChatArena is a Python framework for running language games with multiple LLM agents. It suits researchers and developers studying agent interaction, collaboration, and social behavior, but the project was deprecated in August 2025 and is no longer supported.
Agentarium: Build and Orchestrate AI Agent Simulations
Agentarium is a Python framework for creating AI agents that interact, take context-based actions, and retain memories. Use it to prototype multi-agent scenarios, add custom actions, and save agent states for repeatable experiments.
lighteval: Evaluate Language Models Across Backends
Lighteval is a Python toolkit for running LLM evaluations across local models and remote inference backends. It combines a broad task catalog with custom metrics and detailed sample-level results for teams comparing or debugging model performance.