Software:Lists of open-source artificial intelligence software
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These lists include projects which release their software under open-source licenses and are related to artificial intelligence projects. These include software libraries, frameworks, platforms, and tools used for machine learning, deep learning, natural language processing, computer vision, reinforcement learning, artificial general intelligence, and more.
Agentic AI
- Auto-GPT — experimental open-source autonomous GPT-based agent
- CrewAI – framework for building and orchestrating multi-agent AI workflows
- Hermes Agent — self-improving AI agent developed by Nous Research
- LangChain – framework for integrating LLMs into applications
- OpenClaw — autonomous task-executing AI agent
- OpenHands — AI software development agent
AI-assisted software development
- Codex CLI – AI coding agent and command-line interface developed by OpenAI.[1]
- DeepSeek Coder – large language model designed for code generation and AI-assisted software development.[2]
- Eclipse Theia – integrated development environment and framework with AI-assisted software development features.[3][4]
- GLM – large language model family with capabilities for AI-assisted software development.[5][6]
- Zed – source-code editor with integrated AI-assisted development and agentic coding features.[7]
- Grok Build – Grok Build is SpaceXAI's terminal-based AI coding agent.[8]
AI hardware and inference acceleration
LLM inference and serving frameworks
- llama.cpp — library that can perform inference on various LLMs such as Llama, Mistral, Gemma, DeepSeek or Qwen.[9]
- SGLang – framework for structured generation and high-performance LLM inference and serving
- vLLM – high-throughput inference engine for large language models using techniques such as PagedAttention
- Ollama - a software platform that enables easy deployment and interaction with many large language models locally.
Model formats and optimization toolkits
- ONNX – Open Neural Network Exchange format for interoperability between AI frameworks
- OpenVINO – Intel's toolkit for optimizing deep learning models for edge devices
- TensorRT-LLM — Nvidia toolkit for optimizing and deploying large language models on GPUs
Artificial neural networks
- EDLUT – event-driven neural network simulator for large-scale spiking networks
- Emergent – cognitive modeling platform implementing neural networks
- Encog – machine learning framework for Java and C# supporting neural networks
- JOONE – Java-based neural network framework with modular architecture for learning tasks
- Nengo – Python library for building and simulating large-scale neural systems
- Neuroph – lightweight Java framework for creating neural networks
- OpenNN – C++ library for designing, training, and deploying neural networks
- SNNS – Stuttgart Neural Network Simulator, supports feedforward and recurrent neural networks
Convolutional neural networks (CNNs)
- AlexNet — pioneering CNN for image classification, won the 2012 ImageNet competition[10][11][12]
- VGGNet — deep CNN known for its simplicity and use of 3x3 convolution filters[13]
- Inception — CNN architecture using parallel convolutional layers of different sizes[14]
State-space models
- Mamba – selective state-space model architecture for efficient sequence modeling[15]
Chatbots
Cognitive architectures and AGI platforms
- ACT-R – cognitive architecture for modeling human cognition and developing cognitive agents.[16]
- CLARION – Connectionist Learning with Adaptive Rule Induction On-line, hybrid connectionist/symbolic cognitive architecture.
- OpenCog – project that aims to build an open source artificial intelligence framework
- Soar – cognitive architecture for decision-making and learning in intelligent agents
Computer vision and image processing
- AForge.NET – computer vision, artificial intelligence, and robotics library for the .NET framework
- Dlib – C++ library for computer vision and image processing
- OpenCV — library of programming functions mainly for real-time computer vision
- Point Cloud Library – library for point cloud processing
- Tesseract – optical character recognition
Deep learning frameworks
- BigDL – distributed deep learning library for Apache Spark
- Caffe – deep learning framework focused on speed and modularity
- Deeplearning4j – Java library for deep learning algorithms on the Java virtual machine
- DeepSpeed – deep learning optimization library developed by Microsoft
- fastai – deep learning library built on top of PyTorch
- Fast Artificial Neural Network (FANN) – C library for feedforward neural networks
- Horovod – distributed deep learning framework for TensorFlow, Keras, and PyTorch
- Keras – Python library for artificial neural networks
- Microsoft Cognitive Toolkit – deep learning framework developed by Microsoft Research
- MXNet – deep learning framework for training and deploying deep neural networks
- Neuroph – object-oriented artificial neural network framework written in Java
- OpenNN – artificial neural network library written in C++
- PlaidML – deep learning backend for neural networks and tensor computations
- PyTorch – deep learning framework developed by Meta AI
- PyTorch Lightning – high-level framework built on top of PyTorch for organizing and scaling deep learning models
- TensorFlow – end-to-end open-source platform for machine learning and deep learning developed by Google Brain
- Torch – scientific computing framework with support for machine learning and deep learning algorithms
Machine learning or data mining
- Accord.NET — C# framework for machine learning, statistics, computer vision, and signal processing
- Apache Mahout — scalable machine learning library for big data built on Hadoop and Spark
- Apache SINGA — distributed deep learning and machine learning software
- Apache SystemDS — ML system for the end-to-end data science lifecycle
- CatBoost — machine learning library for gradient boosting on decision trees
- Caffe — Image classification and image segmentation
- Dlib — C++ machine learning and computer vision library
- ELKI — data mining and unsupervised learning software
- fastText — Word embeddings developed by Meta AI
- Flux — machine learning library for the Julia programming language
- Gensim — topic modelling and vector space model toolkit
- JAX — machine learning library for numerical computing and automatic differentiation
- H2O — machine learning and predictive analytics platform
- Infer.NET — probabilistic programming framework for Bayesian inference
- Jubatus — online machine learning and distributed computing framework
- KNIME — modular data pipelining
- LIBSVM — library for support vector machines
- LightGBM — machine learning framework for gradient boosting
- Massive Online Analysis — framework for machine learning and data mining on evolving data streams
- Microsoft Cognitive Toolkit — deep learning framework developed by Microsoft Research
- MindSpore — machine learning and deep learning framework
- ML.NET — machine learning framework for .NET
- mlpack — C++ header-only machine learning library
- MXNet — deep learning framework
- Orange — machine learning, data mining, data visualization, and data analysis
- PyMC — Python framework for Bayesian modeling and probabilistic programming
- Scikit-learn — library built on top of NumPy, SciPy, and matplotlib
- Scikit-multiflow — Python framework for online and stream machine learning
- Shogun — C++ library for large-scale machine learning
- Spark MLlib — machine learning library for Apache Spark
- TensorFlow — machine learning and deep learning platform
- Theano — numerical computation library for machine learning
- Vowpal Wabbit — machine learning system for fast online learning
- Weka — collection of machine learning algorithms for data mining tasks
- XGBoost — machine learning library for gradient boosting
AutoML platforms
- TPOT – tree-based pipeline optimization tool using genetic programming
- Neural Network Intelligence – Microsoft toolkit for hyperparameter tuning and neural architecture search
- MindsDB – AutoML platform that embeds machine learning into SQL databases and applications
Large language models
- Apertus – Swiss National AI Initiative LLM[17]
- BERT – Google LLM
- Cerebras-GPT – Cerebras Systems LLMs[18]
- DeepSeek – R1 and V3 models[19]
- Gemma 4 – Google LLM[20]
- GLM-4.5 and later versions – Z.ai LLMs[21]
- GPT-1, GPT-2, and GPT-OSS – OpenAI LLMs[22]
- GPT-J, GPT-Neo, and GPT-NeoX – EleutherAI LLMs[23]
- Granite – IBM LLMs[24]
- Grok-1 – xAI LLM
- Inkling – Thinking Machines[25]
- Kimi (some versions) – Moonshot AI LLMs
- Mistral (some versions)[26]
- Nemotron 3 – Nvidia open-weight models[27]
- OLMo – Allen Institute for AI LLM
- Phi – Microsoft LLMs
- Qwen (some versions) – Alibaba Cloud LLMs[28]
- Sarvam-M, Sarvam-105B and Sarvam-30B – Sarvam AI LLMs
- Step-3.5-Flash – StepFun LLM
- T5 – Google LLM
- XLNet – Google LLM
Natural language processing (NLP)
- Apache OpenNLP
- Apertium – rule-based machine translation platform.
- ChatScript – natural language engine and dialog management system
- General Architecture for Text Engineering – information extraction
- Gensim – topic modeling and document similarity analysis library
- GloVe – unsupervised learning algorithm for obtaining vector representations of words
- Mallet – Java "Machine Learning for Language Toolkit"
- MontyLingua – libraries and programs for symbolic and statistical NLP for both Python and Java
- Moses – statistical machine translation engine to train statistical models of text from a source language to a target language
- NiuTrans – statistical machine translation
- NLTK – natural Language toolkit for symbolic and statistical NLP
- Probabilistic Action Cores – interpreter for natural-language instructions for robotic applications
- spaCy – Python library
- Spark NLP – text processing library for advanced NLP for Python, Java, and Scala.
- Word2vec – obtaining vector representations of words
Speech recognition systems
- CMU Sphinx
- DeepSpeech
- Julius
- Whisper
Reactive planning
- GOLOG – logic programming language, situation calculus, first-order logical language for reasoning about action and change.
Reinforcement learning frameworks
- KataGo – reinforcement learning agent designed for playing the game of Go
Robotics software
- ArduPilot
- CoppeliaSim
- Gazebo
- Mobile Robot Programming Toolkit
- OpenRTM-aist
- Paparazzi Project
- Player Project
- Python Robotics
- Robot Operating System
- TurtleBot
- Webots
Text to image
- Flux
- Stable Diffusion
Text to speech
Transformer libraries
- Hugging Face transformers library – Python library of pretrained transformer models for NLP, computer vision, speech, and more.[29]
AI-assisted algorithm discovery
- AlphaTensor – DeepMind reinforcement-learning system for discovering efficient matrix multiplication algorithms
Music and audio generation
- Riffusion – generating music and audio using Stable Diffusion.[30]
Knowledge bases and knowledge graphs
- ConceptNet – multilingual commonsense knowledge graph used in natural-language processing and artificial-intelligence applications.[31]
- DBpedia – project that extracts structured knowledge from Wikipedia using an open-source extraction framework.[32]
See also
- Open-source artificial intelligence
- List of artificial intelligence algorithms
- List of artificial intelligence journals and List of artificial intelligence books
- List of artificial intelligence projects
- List of free and open-source software packages for artificial intelligence
- Open weights
- Common Crawl – nonprofit that crawls the web and freely provides its archives and datasets to the public under an MIT License
- Google Colab – an O-IDE Jupyter notebook environment with free access to GPUs and TPUs for machine learning and deep learning development
- Applications of artificial intelligence
References
- ↑ "openai/codex". https://github.com/openai/codex.
- ↑ "deepseek-ai/DeepSeek-Coder". https://github.com/deepseek-ai/DeepSeek-Coder.
- ↑ "eclipse-theia/theia". https://github.com/eclipse-theia/theia.
- ↑ "Theia IDE – AI-Native Open-Source Cloud and Desktop IDE". https://theia-ide.org/.
- ↑ Jiang, Ben (February 11, 2026). "Chinese AI start-up Zhipu releases new flagship model GLM-5". Reuters. https://www.reuters.com/technology/chinas-ai-startup-zhipu-releases-new-flagship-model-glm-5-2026-02-11/.
- ↑ "zai-org/GLM-5". https://github.com/zai-org/GLM-5.
- ↑ "zed-industries/zed". https://github.com/zed-industries/zed.
- ↑ "xai-org/grok-build: SpaceXAI's coding agent harness and TUI". xAI. https://github.com/xai-org/grok-build.
- ↑ ggml-org/llama.cpp, ggml, 2026-04-19, https://github.com/ggml-org/llama.cpp, retrieved 2026-04-19
- ↑ "GitHub - computerhistory/AlexNet-Source-Code: This package contains the original 2012 AlexNet code". Computer History Museum. https://github.com/computerhistory/AlexNet-Source-Code.
- ↑ "How AlexNet Transformed AI and Computer Vision Forever". IEEE Spectrum. 25 March 2025. https://spectrum.ieee.org/alexnet-source-code. Retrieved 14 April 2026.
- ↑ "CHM Makes AlexNet Source Code Available to the Public". 20 March 2025. https://computerhistory.org/press-releases/chm-makes-alexnet-source-code-available-to-the-public/.
- ↑ Dhillon, Anamika; Verma, Gyanendra K. (2020-06-01). "Convolutional neural network: a review of models, methodologies and applications to object detection" (in en). Progress in Artificial Intelligence 9 (2): 85–112. doi:10.1007/s13748-019-00203-0. ISSN 2192-6360. https://link.springer.com/article/10.1007/s13748-019-00203-0.
- ↑ Zhang, Aston; Lipton, Zachary; Li, Mu; Smola, Alexander J. (2024). Dive into deep learning. Cambridge New York Port Melbourne New Delhi Singapore: Cambridge University Press. ISBN 978-1-009-38943-3.
- ↑ "state-spaces/mamba". https://github.com/state-spaces/mamba.
- ↑ "ACT-R 7.30+ Reference Manual". Carnegie Mellon University. https://act-r.psy.cmu.edu/actr7.x/reference-manual.pdf.
- ↑ Allen, Matthew (2025-09-02). "Switzerland launches transparent ChatGPT alternative" (in en). https://www.swissinfo.ch/eng/swiss-ai/switzerland-launches-transparent-chatgpt-alternative/89929269. "Apertus (from the Latin word meaning “open”) leaves nothing to the imagination in this respect. It promises that every nut and bolt is open for public scrutiny along with its design manual and recipe formula."
- ↑ Dey, Nolan; Gosal, Gurpreet; Chen, Zhiming; Khachane, Hemant; Marshall, William; Pathria, Ribhu; Tom, Marvin; Hestness, Joel (2023). "Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster". arXiv:2304.03208 [cs.LG].
- ↑ model weights only
- ↑ "google/gemma-4-31B-it · Hugging Face". 2026-04-02. https://huggingface.co/google/gemma-4-31B-it.
- ↑ Cheng, Evelyn (28 July 2025). "China's latest AI model claims to be even cheaper to use than DeepSeek" (in en). https://www.cnbc.com/2025/07/28/chinas-latest-ai-model-claims-to-be-even-cheaper-to-use-than-deepseek.html.
- ↑ Heath, Alex (2025-08-05). "OpenAI releases a free GPT model that can run on your laptop" (in en-US). https://www.theverge.com/openai/718785/openai-gpt-oss-open-model-release.
- ↑ Black, Sid; Biderman, Stella; Hallahan, Eric; Anthony, Quentin; Gao, Leo; Golding, Laurence; He, Horace; Leahy, Connor; McDonell, Kyle; Phang, Jason; Pieler, Michael; Prashanth, USVSN Sai; Purohit, Shivanshu; Reynolds, Laria; Tow, Jonathan; Wang, Ben; Weinbach, Samuel (2022). "GPT-NeoX-20B: An Open-Source Autoregressive Language Model". arXiv:2204.06745 [cs.CL].
- ↑ "Open sourcing IBM's Granite code models". May 6, 2024. https://research.ibm.com/blog/granite-code-models-open-source.
- ↑ Knight, Will (2026-07-15). "Thinking Machines Lab Drops Its First Model" (in en-US). Wired. ISSN 1059-1028. https://www.wired.com/story/thinking-machines-lab-releases-its-first-model-inkling/. Retrieved 2026-07-20.
- ↑ "Models Overview | Mistral AI Large Language Models" (in en). https://docs.mistral.ai/getting-started/models/models_overview/.
- ↑ Knight, Will (December 15, 2025). "Nvidia Becomes a Major Model Maker With Nemotron 3". Wired. https://www.wired.com/story/nvidia-becomes-major-model-maker-nemotron-3/. Retrieved July 31, 2026.
- ↑ Mo, Liam; Hall, Casey (19 September 2024). "Alibaba accelerates AI push by releasing new open-source models, text-to-video". Reuters. https://www.reuters.com/technology/alibaba-accelerates-ai-push-by-releasing-new-open-source-models-text-to-video-2024-09-19/.
- ↑ "huggingface/transformers". Hugging Face. https://github.com/huggingface/transformers.
- ↑ "riffusion/riffusion-hobby". Riffusion. https://github.com/riffusion/riffusion-hobby.
- ↑ "Copying and sharing ConceptNet". ConceptNet. https://github.com/commonsense/conceptnet5/wiki/Copying-and-sharing-ConceptNet.
- ↑ "dbpedia/extraction-framework". DBpedia. https://github.com/dbpedia/extraction-framework.
External links
- opensource.org/ai – Open Source Initiative
- Data and AI White paper (July 24, 2024) – Open Data Institute
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