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Running AI locally means the model's weights sit on your machine and the processing happens there. Nothing leaves your computer, nothing is billed per message, and it works offline. You need two pieces: a runtime app and an open-weight model.

For non-coders the runtime is a normal desktop app. Ollama, LM Studio, Jan, GPT4All, and Msty are all download-and-click. GPT4All even runs on a plain CPU with no graphics card, and its LocalDocs feature chats with your own files without an account.

The hardware rule of thumb, at the common 4-bit quantization: an 8-billion-parameter model wants about an 8 GB GPU or a 16 GB Mac. Small models (SmolLM3, Qwen's 0.6B-to-4B sizes, Gemma 2B and 4B, Phi-4-mini) run on a CPU-only laptop. The giant open flagships (Kimi K2, DeepSeek's full V-series) are server hardware, not laptop material, open weights or not.

Snapshot of 7 June 2026. 31 entries in this group, about 31 with a free option and 31 that can run on your own hardware. Prices and versions change often, and each name links to its official page. The full directory has search and filters across all categories.

How to Choose

Easiest first run:

LM Studio or GPT4All. Fully graphical: search a model, download, chat. GPT4All needs no GPU at all.

The popular default:

Ollama. One installer, a clean desktop app, and most other local-AI tools know how to talk to it.

Chat with your documents:

GPT4All's LocalDocs and AnythingLLM both do private document Q&A entirely on your machine.

Weak or old hardware:

SmolLM3 (3B), Qwen 0.6B-4B, Gemma 2B and 4B, and Phi-4-mini run on ordinary laptops without a dedicated GPU.

For developers:

llama.cpp is the engine under most of these apps, vLLM serves at production scale, and LocalAI mimics the OpenAI API on your own server.

All 31 Run on your computer Entries

Tool Maker What it is Cost Where it runs Hardware
AnythingLLM Mintplex Labs Runtime app: all-in-one desktop app for chat with docs, RAG, and agents. Free Cloud or local Your PC or Mac
Cohere Command (open) Cohere Open model: enterprise RAG and agent models. Open weights are non-commercial. Open-weight Cloud or local 2x H100. R7B ~8-12GB
DeepSeek (open) DeepSeek Open model: small distilled versions run locally. The flagships need a data center. Open-weight Cloud or local Distills 1.5-8B local. Flagship data-center
EuroLLM EU consortium Open model: European multilingual model across all 24 EU official languages. Open-weight Cloud or local 22B ~16-24GB
Falcon TII (UAE) Open model: UAE family including hybrid-attention and Mamba variants. Open-weight Cloud or local 1-10B laptop to 10GB. 180B server
Gemma Google Open model: Google open family (separate from Gemini), from mobile to server. Open-weight Cloud or local 2-4B phone/laptop. 27B ~24GB
GLM Zhipu AI Open model: Chinese open family, widely served, from local to server scale. Open-weight Cloud or local Smaller ~8-24GB. GLM-5 server
gpt-oss OpenAI Open model: OpenAI first open LLMs since GPT-2. MoE with 128K context. Open-weight Cloud or local 20b ~16GB. 120b ~80GB GPU
GPT4All Nomic AI Runtime app: one-click desktop app. Chat with your own files offline. Free Local Your PC or Mac (CPU ok)
Granite IBM Open model: enterprise small and mid models with transparent training. Open-weight Cloud or local 3B laptop. 8B ~8GB. 30B ~24GB
Jan Menlo Research Runtime app: open-source ChatGPT-style desktop app for local or cloud models. Free Cloud or local Your PC or Mac
Kimi K2 Moonshot AI Open model: large MoE strong on agentic coding. Not laptop-runnable. Open-weight Cloud or local ~1T MoE, data-center only
KoboldCpp Community Runtime: single-file llama.cpp fork with a UI. Popular for writing and roleplay. Free Local Your PC or Mac
Llama Meta Open model: the most widely deployed open family. Llama 4 adds MoE and multimodal. Open-weight Cloud or local 8B ~8GB GPU / 16GB Mac. 70B ~48GB+
llama.cpp ggml-org Runtime: the C/C++ engine behind most local runners. CLI and a server. Developer tool. Free Local Your PC or Mac (CPU or GPU)
Llamafile Mozilla.ai Runtime: packs a model into one executable file you just run. Free Local Your PC or Mac (no install)
LM Studio LM Studio Runtime app: fully graphical desktop app that searches and runs open models. Free Local Your PC or Mac
LocalAI Community Runtime: self-hosted drop-in replacement for the OpenAI and Anthropic APIs. Free Local Your PC or server (CPU ok)
Mistral / Mixtral Mistral AI Open model: French lab with small dense and large MoE open releases. Open-weight Cloud or local 7B ~6GB. Large MoE on a server
MLC LLM MLC AI Runtime: compiles models to run across GPUs, phones, and the browser. Free Local PC, Mac, phone, or browser
MLX Apple Runtime: Apple framework with the fastest token generation on Apple Silicon. Free Local Apple Silicon Mac
Msty Msty Runtime app: polished desktop app with multi-model compare and knowledge stacks. Free + paid Cloud or local Your PC or Mac
Nemotron NVIDIA Open model: NVIDIA family tuned for agentic AI. Nano runs locally. Open-weight Cloud or local Nano ~16-24GB. Ultra data-center
Ollama Ollama Runtime app: popular local runner with a desktop chat app. No terminal needed. Free Local Your PC or Mac
OLMo 3 Allen Institute (Ai2) Open model: truly-open research models with all code, data, and checkpoints. Open-weight Cloud or local 7B ~8GB. 32B ~24GB
Open WebUI Open WebUI Runtime: self-hosted web interface for local and cloud models. Multi-user. Free Cloud or local Your server or PC
Phi Microsoft Open model: small reasoning-strong models built data-quality first. Open-weight Cloud or local 14B ~8-10GB. Mini fits 8GB
Qwen Alibaba Open model: very active family, dense plus MoE, with strong coding variants. Open-weight Cloud or local 8B ~8GB. 32B ~24GB. 235B server
SmolLM3 Hugging Face Open model: small, fully-open model with weights, data, and configs released. Open-weight Cloud or local 3B on a laptop / 4-6GB
text-generation-webui oobabooga Runtime: Gradio web UI for local models with many backends and an API. Free Local Your PC or Mac
vLLM vLLM project Runtime: high-throughput serving engine. OpenAI-compatible. Production tool. Free Cloud or local Server-class GPU(s)

Common Questions

What hardware do I need to run AI locally?

For 7-to-8B models at 4-bit quantization, about an 8 GB GPU or a 16 GB Apple Silicon Mac. For 13-to-14B, 10 to 12 GB. For 30-to-32B, a 24 GB GPU or a 32 GB Mac. Small 1-to-4B models run CPU-only. MoE flagships like Kimi K2 need server hardware regardless of being open-weight.

Is local AI actually private?

The model runs entirely on your machine, so prompts and documents stay there, and GPT4All works offline by default. The privacy boundary is the model runtime, not the apps around it: if you connect a local app to a cloud API, that traffic leaves your machine again.

Are local models as good as ChatGPT?

The models a laptop can run are much smaller than frontier cloud models, and it shows on hard tasks. The gap narrows every year, and for summarizing, drafting, and document Q&A a good 8-to-14B local model handles the work well. The trade is capability for privacy, cost, and offline use.