LM Studio
A desktop app for finding, downloading and chatting with open language models, with a built-in local server for other apps.
- Works offline after setup
- Local API server
- Runs on macOS
A desktop app for finding, downloading and chatting with open language models, with a built-in local server for other apps.
An open-source desktop chat app that runs models offline, keeps conversations as local files and can expose a local API.
A free desktop app for running open models on ordinary laptops, with a feature for chatting with folders of local documents.
A desktop chat app that runs local models and online ones side by side, with split chats for comparing answers.
A self-hosted web chat interface for local model runners such as Ollama, with users, document upload and model switching.
A desktop and mobile chat client that can talk to a local Ollama server as well as hosted model APIs.
A launcher that installs and runs open-source AI apps on your computer with one click, each in its own folder.
A browser-based interface for running local language models with many loaders, sampling settings and extensions.
An open-source, self-hosted chat interface that can connect to local model servers and hosted APIs from one place.
A command-line runner and local server that downloads open models by name and serves them to other apps on your machine.
The C and C++ engine behind many local AI apps, for running quantized GGUF models on CPUs, GPUs and Apple silicon.
Packs a model and its runtime into one executable file that runs on most operating systems without an install step.
A self-hosted server that runs text, image and audio models locally behind an API shaped like common hosted ones.
A single-file runner for GGUF models with a built-in web interface, often used for long-form writing and story sessions.
An array framework from Apple research for running and training models efficiently on Apple silicon memory.
Compiles language models to run natively on laptops, phones and in the browser through one deployment workflow.
A high-throughput serving engine for language models on GPUs, often used to share one strong machine with a team.
A fast serving framework for language and vision models on GPUs, with caching that helps when prompts share long prefixes.
NVIDIA's library for compiling and running language models with kernels tuned for its GPUs.
A cross-platform runtime for models in the ONNX format, with backends for CPUs, GPUs and NPUs on many devices.
Intel's toolkit for optimizing and running models on Intel CPUs, integrated graphics and NPUs.
A fast inference library for running quantized language models on consumer NVIDIA GPUs.
Apple's framework for running models on device across the CPU, GPU and Neural Engine in apps for Apple platforms.
A node-based interface for building image and video generation workflows with open diffusion models on your own GPU.
An image generation app with a layered canvas for inpainting, outpainting and editing, available as a free local edition.
An image generation app for Mac, iPhone and iPad that runs diffusion models fully on the device.
A web interface for image generation that offers a simple prompt tab on top of a ComfyUI backend for advanced work.
A fork of the classic Stable Diffusion web UI that focuses on lower memory use and faster generation.
A web interface for image and video diffusion models with support for several GPU vendors and backends.
A native Mac app that runs Stable Diffusion models converted to Core ML, using the Neural Engine on Apple silicon.
A C and C++ port of OpenAI's Whisper speech recognition model that transcribes audio offline on ordinary hardware.
A dictation app that turns speech into text in any app, with the option to run speech models locally.
A desktop app that transcribes and translates audio files offline with Whisper models.
A Python reimplementation of Whisper on a faster inference engine, using less memory for the same transcripts.
An offline speech recognition toolkit with small models that run on laptops, phones and single-board computers.
A simple Mac and iPhone app that transcribes audio and video files on the device with Whisper.
A small open-weight text-to-speech model that produces natural voices quickly, even on a CPU.
Adds word-level timestamps and speaker labels to Whisper transcripts for interviews and meetings.
A desktop and self-hosted app for chatting with your documents through a local model, with workspaces per project.
An open-source project for asking questions about documents with a local model, with an API for building on top.
An open-source assistant that searches and chats over your notes and documents and can be self-hosted.
An open-source app for private question answering over documents, images and audio with local models.
A clean web interface for chatting with documents that shows the source passages behind each answer.
An open-source engine for document question answering that parses complex layouts such as tables and scanned pages.
A project for chatting with documents entirely on your own machine, with no data leaving the computer.
An NVIDIA demo app for Windows PCs with RTX graphics that answers questions about your local files.
An open-source assistant for VS Code and JetBrains that can use a local model for chat, edits and autocomplete.
A self-hosted code completion server you run on your own GPU, with editor plugins for common IDEs.
An open-source coding assistant and agent that can be self-hosted with your own models.
A VS Code extension for code completion from a llama.cpp server running on your machine.
The largest public host for open model weights, datasets and demos, where most local models are first published.
A model hub run by Alibaba that hosts open models and datasets, including many released by Chinese labs.
Google's model repository on Kaggle, with open models ready to download or try in notebooks.
The single-file model format used by llama.cpp and many local apps, with built-in support for quantized weights.
A file format for storing model weights that loads fast and cannot run hidden code when opened.
A library for fine-tuning open language models faster and with less GPU memory, with ready notebooks.
A configuration-driven tool for fine-tuning open models, from small adapters to full training runs.
A library for 8-bit and 4-bit model weights, used to load and fine-tune large models on smaller GPUs.
Tools built on MLX for running, quantizing and fine-tuning language models on Apple silicon Macs.
A fine-tuning toolkit with a web interface that supports many open model families and training methods.
A terminal monitor for GPU load, memory and processes on Linux, with support for several GPU vendors.
A terminal monitor for CPU, GPU, Neural Engine and power use on Apple silicon Macs.
A small Windows utility that shows graphics card details, video memory use, clocks and temperatures.
A cross-platform benchmark that measures how fast a device runs AI workloads on its CPU, GPU and NPU.
A Windows hardware monitor with detailed sensor readings for temperatures, power draw and memory.
A terminal resource monitor for CPU, memory, disks and processes, with GPU stats on supported systems.
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