In-Depth
Ditch the Cloud: 7 Powerful, Free Local AI Tools
In a set of recent articles, I discussed how to run AI locally on both physical and virtual machines. By running AI models and AI applications locally, you can choose between hundreds of different large language models (the brains behind AI) and gain greater control over where the data is stored, while using excess CPU and GPU resources to reduce the amount of money you spend on cloud-based AI.
In those articles, I used LLMfit to find an LLM suited to the hardware I had, Geekbench AI to quantify the hardware's AI performance and Aipex to monitor the CPU and GPU usage of the systems. For the most part, those articles were theoretical, since most people do not want to run an LLM; they want to do something useful with it. Still, chatbots are only the tip of the iceberg when it comes to running AI-based applications locally, as there are free projects and applications that let you do everything from coding to converting text to speech.
Below is a summary of the ones I have used, and a few others are on my list to use and write about.
LM Studio -- Chatbot Like ChatGPT
LM Studio is a desktop application for running large language models locally rather than relying on a cloud service. Users can download AI models such as Llama, Qwen, Gemma, Mistral or DeepSeek, chat with them through a graphical interface and expose them via an OpenAI-compatible local API for use by other applications. It is used by developers, researchers, writers and AI hobbyists like me who want to work with models locally, use their private data or build applications without sending every request to a hosted AI provider. Its commercial competition includes ChatGPT, Claude, Microsoft Copilot, Google Gemini and paid local AI tools such as Msty.
The project is located on the LM Studio website and is maintained by Element Labs. It runs on Windows, macOS and Linux, though platform support varies by processor type. LM Studio recommends at least 16 GB of RAM and a dedicated GPU with 4 GB or more of VRAM, depending on the LLM you choose. Installation involves downloading the installer for your operating system, launching the application, selecting a model from the built-in catalog, downloading the model files and loading the model for chat or API use.
AnythingLLM -- Private Chatbot Like NotebookLM
AnythingLLM is an AI workspace for building private chat systems, document assistants and retrieval-based AI applications. Users can upload their personal files and data, connect data sources, organize information into workspaces and ask questions about that content using either local or cloud-based LLMs. Looking around, I found that it is widely used for internal knowledge bases, research collections, help desk content, private document search and agentic workflows. Its commercial competition includes ChatGPT Team and Enterprise, Microsoft Copilot Studio, Google Gemini for Workspace, Glean, Notion AI and Google NotebookLM.
The project is located on the AnythingLLM website and in the Mintplex Labs GitHub repository. It can be installed as a desktop application or deployed as a self-hosted server. The resources it requires depend on whether it uses cloud models or local models. Still, a modern processor, enough storage for documents and embeddings and 16 GB of RAM provide a reasonable starting point for local use. Installation can be done by downloading the desktop installer or by deploying the server version with Docker, then connecting it to a model provider such as Ollama, LM Studio, OpenAI, Anthropic or another supported AI service.
Cursor -- AI Coding Agent Like Claude Code
Cursor is an AI-powered code editor based on Visual Studio Code. It helps developers write, explain, refactor, debug and review code while understanding the project's context. Developers use it as a primary coding environment where they can request changes in natural language, generate new files, review existing code and interact with AI agents in the editor and related tools. Its commercial competition includes GitHub Copilot and JetBrains AI Assistant, as well as Tabnine Enterprise, Sourcegraph Cody, Replit Agent, Claude Code and OpenAI Codex.
The project is located on the Cursor website and is developed by Anysphere. It runs on Windows, macOS and Linux, and its local resource requirements are similar to those of a modern code editor. However, the AI features depend on cloud access and account configuration. Installation involves downloading the installer from Cursor, signing in, choosing a plan or model access option and importing existing Visual Studio Code extensions and settings if desired. Once installed, you open a software project and allow Cursor to index the codebase so its chat, edit and agent functions can work with the project context.
I do need to note that while Cursor is a local application/IDE, its AI processing primarily relies on hosted cloud APIs (OpenAI/Anthropic) unless specifically configured to proxy to a local server.
OpenCode -- An AI Coding Agent Like Claude Code
OpenCode is an open-source AI coding agent that runs in a terminal, IDE or desktop environment. It helps developers inspect repositories, make code changes, run commands and work through software tasks with support from large language models. It is aimed at users who want an AI coding assistant that is more transparent and configurable than a closed commercial tool. Its commercial competition includes Claude Code, OpenAI Codex and GitHub Copilot, as well as Cursor, Replit Agent, JetBrains AI Assistant and Devin.
The project is located on the OpenCode website and in its public source repository. It can run on macOS, Linux and Windows. On Windows, it looks like users often use Windows Subsystem for Linux (WSL) for the terminal version. The tool's resource requirements are modest, but it needs access to a model provider such as Anthropic, OpenAI, Google, GitHub Copilot or, in my case, a local model service. Installation can be done with the official install script, Node package managers, Homebrew, Chocolatey, Scoop or Docker, or by downloading a desktop build and connecting the tool to a model provider.
OmniVoice -- Text to Speech Like ElevenLabs
OmniVoice is a multilingual text-to-speech and voice-cloning project that can generate speech from text and create a synthetic voice from a short reference recording. It supports many languages and can be used for voice design, accessibility tools, narration and dubbing, as well as prototypes and speech-generation research. Developers use it via Python APIs, command-line tools or a local web interface. Its commercial competitors include ElevenLabs, PlayHT and Resemble AI, as well as Murf, Descript, Azure AI Speech, Amazon Polly and Google Cloud Text-to-Speech.
The project is located in the K2 FSA OmniVoice GitHub repository and on Hugging Face. It requires Python, PyTorch and enough compute to run speech-generation models, with NVIDIA GPUs, Apple Silicon and Intel Arc GPUs listed as supported options. CPU-only use may work for some tasks, but it is not ideal for real-time or high-volume work. Installation generally starts with creating a fresh Python environment, installing PyTorch for the target hardware, installing OmniVoice with pip or from GitHub and then running the local demo or using the Python API to generate speech.
Open Design (Claude Design, Canva)
Open Design is an open-source AI design workspace that connects local coding agents and model providers to design workflows. It is used to create landing pages, dashboards, slide concepts, brand systems, prototypes and design artifacts through prompts and reusable design systems. Rather than being a single hosted design service, it works as a local design layer that can use agents such as Claude Code, Codex, Cursor, Gemini CLI, OpenCode and others. Its commercial competitors include Claude Design, Figma, Canva and Framer, as well as v0, Bolt, Lovable and other AI-assisted design and app-generation tools.
The project is located on the Open Design website and on the nexu.io Open Design GitHub repository. It is designed as a local-first desktop and daemon-based project, so users need a supported desktop operating system, Node 24 for some deployment scenarios, local storage for generated files and credentials for the AI provider or agent they choose to use. Installation usually involves downloading the desktop app or installing from the source repository, signing in or adding model credentials, selecting an agent and giving the tool access to the project files or design systems that it will use.
Open Notebook (Notebook LM)
Open Notebook is an open-source AI research and note-taking platform that lets users collect sources, summarize information, chat with documents, manage notes and generate audio-style content from research material. It supports content such as links, PDFs, text files, presentations, YouTube content and other research inputs. It is used by students, researchers, writers, analysts and technical professionals who want more control over their research workflow and data than a fully hosted tool provides. Its commercial competitors include Google NotebookLM and Notion AI, as well as Microsoft OneNote with Copilot, Evernote AI, Mem, Craft AI and ChatGPT-based research workflows.
The project is located on the Open Notebook website and in the lfnovo Open Notebook GitHub repository. It is self-hosted and can be installed with Docker, from source or manually. The resources required depend on the selected model provider and the size of the user's document library. Still, a modern system with sufficient storage, memory and network access to model APIs is a practical starting point. Installation usually involves using Docker Compose for the fastest setup or cloning the repository, installing the required dependencies, configuring model providers and then creating notebooks and importing documents.
Final Thoughts
I am constantly surprised at the pace of AI-based projects and how quickly local AI, coding assistants, voice tools, design platforms and research applications are evolving. After looking into these tools, LM Studio and AnythingLLM stood out as excellent tools for running and organizing AI locally, with LM Studio focused on downloading and using large language models on a personal computer and AnythingLLM focused on building private workspaces, document search and retrieval-based assistants. Cursor and OpenCode focus on software development, with Cursor offering a polished AI-enabled code editor and OpenCode providing an open-source coding agent that can work from the terminal, desktop or development environment.
For my personal creative projects, I looked at OmniVoice, Open Design and Open Notebook. Together, these tools show how AI is developing and moving into voice creation, visual design and research workflows. OmniVoice provides text-to-speech and voice-cloning capabilities that may rival commercial services such as ElevenLabs and Azure AI Speech. Open Design offers an open-source alternative to tools such as Figma, Canva, Claude Design and v0. At the same time, Open Notebook competes in the same space as Google NotebookLM, Notion AI and Microsoft OneNote with Copilot.
Overall, these projects show that many AI capabilities that once required expensive cloud-based commercial platforms can now be run locally or deployed in self-hosted environments or combined with a user's preferred model provider. However, the proof of the pudding is in the eating, so I'll be putting these tools through their paces on the moderately priced laptop, the Lenovo P16 Gen 3, which has a midrange GPU (RTX PRO 3000 Blackwell GPU and 12 GB of GDDR7 VRAM) that I just reviewed.