Want to run LLM locally on your own computer without relying on cloud services? Many users today prefer to run LLM locally for better privacy, faster response times, and complete control over their AI models. You are definitely not the only one. Lots of people are tired of sending their chats to some random server far away — and honestly, that makes total sense. Privacy, speed, or just skipping those monthly API bills — there are solid reasons to go local in 2026.
So we put together a list of the top 15 tools that let you do exactly that. Run powerful AI models offline, on your own hardware, no internet needed.
Some of these are super easy to pick up, even if you’re a total beginner. Others are built more for developers. And a few are just straight-up impressive.
You’ll find free options, paid ones, and open source tools in the mix. There’s something here for pretty much everyone. Let’s get into it.
Table of Contents
Comparison of Top 15 Tools to Run LLM Locally on Your PC (Free & Paid) — 2026
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Free
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Freemium
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Web, Windows, macOS, Linux
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Freemium
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Web, Windows, macOS, Linux, iOS, Android
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Open Source
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Linux, Windows, macOS, Android, Docker
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Open Source
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Linux, Windows
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Open Source
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Windows,macOS,Linux
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Open Source
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Web, Windows, macOS, Linux
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Open Source
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Open Source
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Freemium
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Windows, macOS
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One-time Purchase
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Free
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1. Ollama: Ollama is a super friendly tool that lets you run LLM locally using quick and easy commands on your computer.
Ollama is probably the most popular way to run LLM locally right now. and honestly, it’s easy to see why. It is a command line tool that makes pulling and running open source AI models feel almost like installing a regular app. You type one command, and boom Llama 3, Mistral, Phi or Gemma is running right on your machine. It’s built for developers, but even beginners pick it up pretty fast.
What makes it stand out is how clean and simple everything feels. The model library is solid, updates drop regularly, and the community’s genuinely active. It supports offline AI tools on Windows, Mac, and Linux. And it connects nicely with other tools like Open WebUI, which is a big plus.
So if you want to run AI without internet and don’t know where to start just start here. Ollama makes local AI on PC way less intimidating than it sounds.
Key Features
- One-command model download — just run `ollama pull llama3` and you’re set, no fuss at all
- Supports dozens of the best Ollama models including Llama 3, Mistral, Phi-3, Gemma, and more
- REST API built in — makes it easy to connect to other apps and build your own local AI assistant
- Very lightweight on setup — no heavy GUI, runs clean in the background as a local server
- Works as a local AI for coding — pair it with a code editor extension and you’ve got a solid offline code generator
- Active model library — new models get added regularly, so you’re never stuck with outdated options
Pros & Cons
Pros & Cons
Pros
- Free and open source — zero cost to get started with local AI on Windows or Mac
- Setup takes maybe 5 minutes, which is genuinely impressive for what it does
- Works great as a backend for other tools like Open WebUI or AnythingLLM
- Model management is clean — pull, list, and delete models with simple commands
- Strong community support and regular updates keep it feeling fresh
Cons
- Command-line only by default — if you need a GUI, you'll have to pair it with something else
- No built-in chat interface, so it's not the most beginner-friendly standalone experience
- Some larger models need a decent GPU to run at a usable speed
Device Compatibility:
Works on Windows, macOS, and Linux. GPU acceleration supported for NVIDIA and Apple Silicon (M1/M2/M3). Yeah, it runs well across all the major platforms — probably the most cross-platform friendly tool on this list.
Pricing:
Completely free. Open source. No plans, no subscriptions, no catch. It’s one of those rare tools where the free local LLM experience actually feels complete.
Customer Support:
Community-driven support via GitHub Issues and Discord. There’s solid documentation on the official site too. No live chat or email support, but the GitHub community is responsive enough that most questions get answered pretty quickly.
2. LM Studio: LM Studio has a beautiful visual interface that makes it incredibly simple to choose and run LLM locally in minutes.
LM Studio is pretty much the go to tool when someone wants to run LLM locally without relying on cloud services. It’s a full desktop app with a clean, simple layout you open it, browse the model library, download what you want and just start chatting. No typing commands, no messing with config files, nothing like that. It’s built for people who want local AI but don’t want to feel like they’re doing a coding project every time they use it.
And the best part is you’ll be up and running in under ten minutes on most machines, which is kind of hard to beat for a tool this powerful. It also has a built-in local server mode, so developers can use it like an API endpoint which means it works great for both regular users and people who actually know how to code.
A lot of folks compare it to Ollama, but Ollama vs LM Studio really comes down to one thing do you prefer a visual interface or a command line? Both are excellent tools, just built for different kinds of users.
Key Features:
- Beautiful desktop interface — model browsing, downloading, and chatting all in one place
- Built-in Hugging Face model browser — search and download GGUF models without leaving the app
- Local server mode — runs a local API so you can use it as an LM Studio alternative for OpenAI-compatible apps
- Hardware detection — automatically adjusts settings based on your CPU, RAM, and GPU
- Model profiles and presets — save settings for different models so you’re not tweaking every time
- Works great for local AI for coding — can be paired with VS Code extensions easily
Pros & Cons
Pros & Cons
Pros
- No technical knowledge needed — genuinely one of the easiest setups for offline AI tools
- The model browser makes finding the best local AI models straightforward
- Local API mode is super useful for developers who want to build on top of it
- Regular updates with a polished, well-maintained UI
- Free for personal use — which is a great deal given how full-featured it is
Cons
- Can feel a bit heavy to launch compared to lighter CLI tools
- The free version has some limitations for commercial use — worth checking the license
- Occasional UI bugs on some Windows configurations, though nothing show-stopping
Device Compatibility:
Available on Windows, macOS (including Apple Silicon), and Linux. GPU acceleration works with NVIDIA CUDA and Apple Metal. Runs decently even on CPU-only machines with smaller models.
Pricing:
Free for personal use. There’s a paid plan for commercial use — pricing details are on the official LM Studio website, so worth checking there for the latest. The free tier covers everything most personal users need.
Customer Support:
Documentation is well-written. Community support via Discord and GitHub. No live chat, but the Discord server is pretty active and the team shows up there regularly.
3. GPT4All: GPT4All is a free desktop app that helps you run LLM locally and chat privately with your own documents.
GPT4All is one of the original tools for running a free local LLM on your PC. It was among the first projects to make offline AI setups actually doable for regular people — and it’s gotten a lot better since then.
The desktop app is clean and simple. You pick a model, download it, and start chatting. That’s pretty much it. Think of it like an offline ChatGPT you run entirely on your own machine.
What makes it stand out is privacy. Nothing leaves your computer — ever. It’s also got this LocalDocs feature where you can chat with your own files, like PDFs or text docs. Super handy for personal stuff.
It’s not the flashiest tool out there. But honestly? It does exactly what it says it’ll do, and it does it reliably. If you want to run AI without internet, GPT4All is a solid pick.
Key Features:
- LocalDocs feature — lets you chat with your own documents without any data leaving your PC
- Curated model library — pre-vetted models that are known to work well, so less guesswork
- Simple chat interface — clean, minimal, and easy to use even if you’ve never touched an AI app before
- Fully offline — designed from the ground up to be a secure local AI tool with zero cloud dependency
- Supports CPU-only machines — you don’t need a GPU to run most of its models
- Cross-platform — works across all major desktop operating systemsGPT4All is one of the original tools that helped users run LLM locally on their PCs.
Pros & Cons
Pros & Cons
Pros
- One of the best free AI models for PC options out there — completely free to use
- LocalDocs makes it genuinely useful as a local AI productivity tool
- Great for users who are serious about private AI tools and data security
- No account needed, no login, no cloud sync — just pure local AI
- Runs on older hardware better than most tools on this list
Cons
- Model selection is more curated, so you won't find every model that's out there
- The UI feels a bit dated compared to newer apps like LM Studio
- Not as developer-focused — limited API or integration options
Device Compatibility:
Windows, macOS, and Linux supported. CPU-only mode works well, with optional GPU acceleration for faster responses.
Pricing:
Completely free. No premium tier, no paid plan. It’s open source and community supported — a solid choice if you want free local LLM capabilities without any strings attached.
Customer Support:
GitHub Issues and community forums are the main support channels. Documentation covers the basics well. No live chat or email support, but the community is genuinely helpful.
4. Jan.ai: Jan.ai is an open-source tool that turns your computer into an AI helper so you can run LLM locally offline.
Jan.ai is kind of a new face in the local AI world. But it’s already made a strong impression. It’s an open source desktop app that looks and feels modern — like a polished tool you’d actually want to use. You can grab models from Hugging Face or its built-in hub. Run them locally. Or even connect to remote APIs like OpenAI if you want to mix things up. Not bad for a free app.
What’s cool is that Jan.ai feels built for the long haul. The team is active. The interface keeps getting better. And the extension system means it’ll grow more powerful over time.
So if you’re looking for a local chatbot for PC that feels like a real product — not just some hobby project — Jan.ai fits that description really well.
Bottom line? It’s one of the best local LLM options out there. You can run LLM locally, keep things private, and enjoy a clean design. No internet needed. Just a solid, free tool.
Key Features:
Threads and conversation management — keeps your chats organized, which sounds small but matters a lot day to day
Built-in model hub — browse and download local AI models without leaving the app
Extensions system — expand functionality with community-built add-ons
Remote API support — connect to OpenAI, Groq or other APIs alongside your local models
Open source codebase — fully auditable if you care about what’s running on your machine
Clean modern UI — probably one of the nicest-looking local AI software options available
Pros & Cons
Pros & Cons
Pros
- Free and open source — works great as a private AI tool right out of the box
- Modern interface that actually keeps up with commercial AI apps in terms of feel
- Flexible — run AI locally or mix in remote APIs depending on what you need
- Regular updates with a clearly active development team
- Good for non-technical users who still want control over their AI setup
Cons
- Extension ecosystem is still growing — not as mature as some other platforms yet
- Can feel slightly slower to load compared to more lightweight CLI tools
- Documentation is decent but could be more detailed in places
Device Compatibility:
Windows, macOS, and Linux supported. Works with NVIDIA GPUs and Apple Silicon. Also runs in CPU-only mode for lighter models.
Pricing:
Free and open source. No paid tiers currently. It’s one of the more complete free offerings for local AI on Windows and other platforms.
Customer Support:
Discord community, GitHub Issues, and documentation on the official site. The Discord is reasonably active and the team does respond to issues. No traditional support tickets or live chat.
5. AnythingLLM: AnythingLLM lets you build your own workspace and run LLM locally to chat with entire folders of your files.
AnythingLLM is the tool to grab when you want to run a local LLM and actually chat with your own data. It’s a full self-hosted AI setup think documents, workspaces, agents, multi-user support all on your own machine. It’s a bit more complex than a basic chat app. But that extra setup gets you a ton of useful features.
We’re talking RAG, custom agents, and workspace organization all built right in. So it’s not just a chat tool. It’s more like a serious productivity setup for local AI.
And here’s what makes it really stand out. You can create separate workspaces for different projects, drop in PDFs, websites, even YouTube transcripts and chat with all of it. Pretty powerful stuff.
It also connects to Ollama, LM Studio, or any OpenAI-compatible backend. So it works with whatever model setup you’ve already got going.
Key Features:
- Document ingestion (RAG) — upload PDFs, docs, and websites and chat with them locally using your own AI
- Multi-workspace support — keep different projects and document sets completely separate
- Agent mode — build AI agents that can browse the web, run code, and more
- Multi-user support — great for small teams who want a self-hosted AI tools setup
- Works with any backend — connects to Ollama, LM Studio, LocalAI or remote APIs
- Vector database built in — no need to set up external infrastructure for embeddings
Pros & Cons
Pros & Cons
Pros
- One of the most complete self-hosted AI tools available for free
- RAG support is genuinely excellent and easy to set up compared to building it yourself
- Flexible backend support means it works with your existing local AI setup
- Active development with new features added regularly
- Great for local AI productivity tools use cases that go beyond simple chat
Cons
- Setup is more involved than simple apps — takes some time to configure properly
- The UI can feel dense if you're just looking for a basic chat experience
- Heavier resource footprint than lighter alternatives
Device Compatibility:
Runs on Windows, macOS and Linux via desktop app or Docker. Browser-based UI works on any device once the server is running. GPU acceleration depends on your chosen model backend.
Pricing:
Free and open source for self-hosting. There’s also a cloud-hosted version with paid plans — check the official AnythingLLM site for current pricing. The self-hosted version is fully free.
Customer Support:
Documentation is pretty thorough. Discord community and GitHub Issues available. For the paid cloud version, standard support channels apply. No live chat on the free tier.
6. Open WebUI: Open WebUI gives you a sleek, ChatGPT-like interface that connects to your computer to run LLM locally with ease.
Open WebUI is pretty much what you get when someone takes the ChatGPT-style interface and makes it work for local AI models. It’s a web based tool that connects with Ollama and OpenAI compatible APIs, giving you a clean and familiar way to run LLM locally on your own PC. If you’ve ever felt Ollama needed a better interface, this is exactly that.
Getting started takes a little setup. You will need Ollama running first, then install Open WebUI using Docker or Python. It’s not the quickest setup, but it’s still simple enough if you follow the steps. Once everything is running, the whole experience feels smooth and easy to use.
The interface looks modern, works in your browser, and feels a lot like ChatGPT. You can switch models during a chat, save conversation history, and create custom system prompts. It’s a pretty complete setup for anyone who wants local AI on PC.
For many users looking for the best local LLM experience, Open WebUI is an easy choice. It helps you run AI without internet, supports free local LLM models and gives you a polished way to use offline AI tools every day.
Key Features:
- ChatGPT-style interface — familiar layout that anyone comfortable with modern AI chat apps will get immediately
- Connects to Ollama and any OpenAI-compatible backend — flexible and easy to extend
- Multi-user mode — supports user accounts and role-based access for team setups
- Model switching in-chat — swap between different local AI models mid-conversation
- System prompt customization — configure exactly how your local AI assistant behaves
- RAG support — upload documents and use them as context in your chats
Pros & Cons
Pros & Cons
Pros
- Probably the best-looking interface available for running models through Ollama
- Entirely free and open source — solid choice for a local AI for Windows or Linux server setup
- Feature set rivals commercial apps — model management, image generation support, and more
- Active community with fast update cycles
- Works great on a local network, so you can access it from other devices
Cons
- Requires Docker or Python setup to install — slightly more technical than plug-and-play apps
- Needs Ollama or another backend running separately — it's a front-end, not standalone
- Can feel like overkill if you just want a simple chat interface
Device Compatibility:
- Runs as a web app on any browser — so Windows, Mac, Linux, tablets, phones. The server itself runs on any machine that supports Docker. GPU support depends on the connected backend.
Pricing:
Free and open source. There’s also a cloud-hosted Open WebUI service with paid plans for people who don’t want to self-host — pricing available on their site.
Customer Support:
Documentation is excellent — probably the most comprehensive of any tool on this list. Discord and GitHub support available. No live chat for the free version.
7. llama.cpp: This clever tool is built for speed and helps regular computers run LLM locally without needing a pricey graphics card.
llama.cpp
Run large language models locally with fast, portable, hardware-optimized C/C++ inference.
llama.cpp is where things get serious. It’s not an app with a GUI — it’s a C++ inference engine that lets you run large language models directly on CPU (and GPU) with impressively low resource usage. This is the engine that powers a lot of other tools on this list behind the scenes. If you want maximum control, maximum performance, and don’t mind working from the terminal, llama.cpp is genuinely one of the most impressive open source LLM projects out there.
The reason developers love it is that it introduced GGUF quantization, which lets you run models that would otherwise require a much bigger GPU. A 7B parameter model that might need 16GB of VRAM can run on CPU with 8GB of RAM in a quantized form. That’s a big deal. It’s not for everyone, but if you’re into building things on top of local AI or need a lightweight local LLM backbone, this is foundational knowledge.
Key Features:
Highly optimized C++ inference — fast, efficient, and works on surprisingly modest hardware
GGUF model format support — the standard format for quantized local AI models
CPU and GPU support — runs on NVIDIA CUDA, Apple Metal, AMD ROCm, and more
HTTP server mode — exposes a local API, making it work like any OpenAI-compatible endpoint
Powers many other tools — LM Studio, GPT4All, and others use llama.cpp under the hood
Lightweight and portable — compiles to a single binary, no heavy dependencies
Pros & Cons
Pros & Cons
Pros
- Extremely efficient — runs solid local AI models on hardware that other tools struggle with
- The foundation of the lightweight local LLM ecosystem — understanding it helps with everything else
- Cross-platform and actively maintained with frequent updates
- Free, open source, and truly community-driven
- Great for building custom local AI setups without all the extra overhead
Cons
- Command-line only — no GUI at all, which is a non-starter for many users
- Steeper learning curve than everything else on this list
- Getting optimal performance requires understanding quantization settings and launch flags
Device Compatibility:
- Windows, macOS, Linux — plus mobile and embedded platforms with some extra setup. GPU support spans NVIDIA, AMD, Intel Arc, and Apple Silicon. Probably the broadest hardware support of any tool here.
Pricing:
- Completely free and open source under the MIT license. No paid version — just download, compile and run.
Customer Support:
GitHub Issues and community discussions are the main channels. The codebase has excellent comments, and there are many community tutorials and guides. No formal support.
8. vLLM: vLLM is an incredibly fast engine designed to run LLM locally for big projects that need to handle lots of tasks.
vLLM isn’t really like the other tools here. Most local AI tools are built for one person chatting at a time — vLLM is different. It’s made to handle a ton of requests all at once, without slowing down. So if you are building something for multiple users, or self-hosting a real AI service, this one’s for you.
And no, you don’t need a whole server room for it. Plenty of developers run vLLM at home on a single NVIDIA GPU. It uses a trick called PagedAttention, which makes the model use memory way smarter. Less waste, better speed.
Sure, it sounds intimidating at first. But honestly? Once it’s running, you kind of forget how complex it was to set up. It just works. Think of vLLM as the powerful engine under the hood. When you need your local AI to run fast and handle real traffic — this is the tool you want.
Key Features:
- PagedAttention memory management — dramatically more efficient GPU memory use compared to standard inference
- OpenAI-compatible API — drop-in replacement for any app expecting an OpenAI-style API endpoint
- High-throughput batch processing — handles many simultaneous requests efficiently
- Supports a wide range of open source LLM models — Llama, Mistral, Mixtral, Falcon, and more
- Continuous batching — improves GPU utilization significantly for server deployments
- Quantization support — runs compressed models for better performance on consumer GPUs
Pros & Cons
Pros & Cons
Pros
- Best-in-class throughput for serving local AI models — nothing beats it for that use case
- OpenAI API compatibility makes integration with existing tools seamless
- Actively developed with strong academic and industry backing
- Great for anyone building a proper self-hosted AI tools setup at scale
- Free and open source
Cons
- Primarily requires NVIDIA GPUs — AMD support exists but is more limited
- Not a beginner tool — expects familiarity with Python environments and server setup
- Overkill for single-user personal use cases
Device Compatibility:
- Primarily Linux with NVIDIA CUDA for best performance. Limited Windows support (WSL works). Experimental AMD ROCm support available. Not really designed for macOS.
Pricing:
Free and open source under the Apache 2.0 license. No paid tiers.
Customer Support:
Documentation is thorough and well-maintained. GitHub Issues and community Slack channel available. No paid support option officially.
9. LocalAI: LocalAI acts as a free helper that lets you run LLM locally as a full replacement for expensive online AI services.
LocalAI is honestly one of the most ambitious tools on this whole list. It’s a self-hosted server that works just like the OpenAI API but everything runs locally on your machine. Text, images, audio, embeddings it does all of it. No internet needed, no data leaving your PC.
The coolest part? Any app that normally works with OpenAI can just point to LocalAI instead. Pretty much a straight swap. Run everything offline without changing much on your end.
And it supports a ton of backends under the hood llama.cpp, whisper.cpp, stable diffusion and more. So it’s less of a single tool and more like a control center for all your local AI stuff.
Setting it up does take some effort though. It’s not plug-and-play. But for developers who want a fully self-hosted AI setup, LocalAI is probably the most complete free local LLM option out there right now.
Key Features:
Drop-in OpenAI API replacement — same endpoints, same structure, fully local and offline
Multi-modal support — text, image generation, audio transcription, embeddings, all in one server
Backend agnostic — uses llama.cpp, whisper.cpp, and others depending on the task
Docker-friendly — straightforward to deploy in containers, great for self-hosted setups
No data leaves your machine — built around the concept of private AI tools from the ground up
GPU and CPU support — flexible across different hardware setups
Pros & Cons
Pros & Cons
Pros
- The only tool here that seriously tries to replicate the full OpenAI API surface locally
- Multi-modal capabilities are genuinely impressive for a free self-hosted project
- Docker deployment makes it very portable across different machines and environments
- Great option for developers building local AI software that needs to avoid cloud APIs
- Strong community with active development
Cons
- Configuration can get complex, especially for multi-modal setups — not a five-minute install
- Documentation has improved but still has gaps in places
- Resource requirements scale with how much you're trying to do simultaneously
Device Compatibility:
- Primarily Linux via Docker, but Windows (Docker Desktop) and macOS work too. GPU support via CUDA and Metal. CPU-only mode is available for lighter tasks.
Pricing:
- Free and open source under the MIT license. No paid tiers.
Customer Support:
GitHub Issues, community Discord, and documentation available. No live support, but the community is active and helpful for most questions.
10. Text Generation WebUI: This tool gives you a handy web page loaded with cool settings to customize how you run LLM locally on your PC.
Text Generation WebUI
Feature-rich browser interface for running and customizing local LLMs
Text Generation WebUI most people just call it “oobabooga” after its creator is a browser-based tool for running local AI models. It’s really built for people who like to tinker. You get a ton of control over how models load, what format they’re in, and how everything runs. It’s kind of the power-user pick for offline AI tools.
It’s super popular in the roleplay and creative writing communities. But honestly, it’s useful for way more than that. The extension library is pretty massive character personas, memory systems, API access, and a lot more.
And the flexibility here is hard to beat. So many model formats, so many ways to set things up. It’s one of the most customizable free local LLM tools out there.
Getting it running does take a little patience though. It’s not the easiest setup. But once it’s working? You’ve got a seriously capable local AI platform at your fingertips.
Key Features:
Supports many loading backends — transformers, llama.cpp, ExLlama, AutoGPTQ, and more
Rich extension ecosystem — community extensions for everything from API servers to persona management
Notebook mode — lets you write prompts more like a document editor than a chat interface
Character and persona support — great for roleplay and creative AI uses
Fine-grained generation settings — temperature, top-p, repetition penalty — full control over outputs
API mode — exposes endpoints so other tools can connect to it
Pros & Cons
Pros & Cons
Pros
- Most flexible model format support of any tool on this list — supports nearly everything
- Extension community keeps adding new capabilities all the time
- Great for creative writing, roleplay, and experimental AI use cases
- Free and open source with a massive user base
- Runs well once configured — stable and reliable for long sessions
Cons
- Setup process is more involved than most tools here — expect to spend time on it
- The UI can feel a bit cluttered once you start adding extensions
- Not the right choice if you just want a quick, simple local chatbot for PC
Device Compatibility:
Windows, macOS, and Linux supported. GPU support for NVIDIA, AMD, and Apple Silicon depending on the backend selected. CPU-only mode available.
Pricing:
- Free and open source. No paid version exists — entirely community maintained.
Customer Support:
Extensive community wiki on GitHub, Reddit community, and Discord. The community is very large, so finding help for most problems is usually pretty doable. No official support.
11. Llamafile: Llamafile turns a complex AI model into a single file you can click to run LLM locally on almost any computer.
Llamafile comes from Mozilla and takes a genuinely different approach to running AI locally. Instead of installing software and then downloading models separately, llamafile bundles the model and the inference runtime into a single executable file. You download one file, double-click it (or run it from the terminal), and you have a running local AI assistant. That’s it, no installs, no dependencies and no setup at all.
It sounds almost too simple, but that’s the point. Mozilla built this as a way to make local AI models as accessible as possible — something you could share with someone who has no technical background and they’d be up and running in thirty seconds. The files are bigger since the model is baked in, but for ease of use, nothing on this list comes close.
Key Features:
Single executable file — the entire model and runtime in one file, no installation required
Runs on any major OS — the same file works on Windows, Mac, and Linux
Built-in web interface — opens a local browser UI automatically when you run it
Also works as a CLI tool — use it in terminal mode if you prefer
Mozilla-backed — thoughtful engineering behind the simplicity
Great for sharing — hand a llamafile to anyone and they can run AI locally immediately
Pros & Cons
Pros & Cons
Pros
- Easiest setup of anything on this list — absolutely zero installation steps
- Perfect for beginners who want to try local AI without any technical barrier
- The web UI that opens automatically is clean and functional
- Cross-platform in the truest sense — one file, any OS
- Free and open source
Cons
- File sizes are large since the model is bundled in — can be multiple gigabytes per file
- Less model variety compared to tools with separate model libraries
- Not great for managing or switching between many models
Device Compatibility:
- Windows, macOS, and Linux — all from the same file. GPU acceleration supported where available, but CPU-only mode works well too.
Pricing:
- Free and open source. Models are also freely downloadable. No paid tier.
Customer Support:
GitHub repository and Mozilla community. Documentation is clear for the simple use case it’s designed for. No formal support channels.
12. KoboldCpp: KoboldCpp is a lightweight tool that makes it easy to run LLM locally, especially for AI storytelling and roleplay fun.
KoboldCpp started as a tool for creative writing and interactive fiction fans. It’s built on top of llama.cpp but comes with a browser-based UI included. Over time it’s grown into a pretty full-featured local AI option. And yeah, it’s gotten a lot more polished too.
The UI leans toward storytelling and roleplay stuff. But it works just fine as a general-purpose local model runner. Don’t let that fool you into thinking it’s limited.
What really makes KoboldCpp stand out is how easy it is to get going. No Docker, no Python setup, nothing like that. Just download the file, point it at your model, and run. That’s pretty much it.
So if Text Generation WebUI felt too complicated, but GPT4All feels a bit too basic — KoboldCpp is kind of the sweet spot in between. It’s a solid free local LLM pick for almost anyone.
Key Features:
Single executable — no complex installation, just download and run against a model file
Browser-based UI — accessible from any device on your local network
Story and adventure modes — specialized modes for interactive fiction and roleplay
Supports GGUF and legacy GGML models — flexible model format support
Context length controls — fine-tune how much conversation history the model considers
Streaming output — text appears as it’s generated, just like in commercial AI chat apps
Pros & Cons
Pros & Cons
Pros
- Very easy setup compared to more technical alternatives — genuinely approachable
- Great for creative writing, story generation, and text-based games
- Works well as a general chat interface too — not limited to fiction use cases
- Free and open source with frequent updates
- Runs well on CPU-only machines with appropriately sized models
Cons
- UI design is functional but not the most modern-looking option available
- Primarily designed for single-user local use — not built for multi-user setups
- Advanced configuration options can feel a bit scattered in the interface
Device Compatibility:
- Windows, macOS, and Linux. GPU acceleration available for NVIDIA and AMD. CPU-only mode runs well on most machines.
Pricing:
- Completely free and open source. No paid version.
Customer Support:
GitHub Issues and community Discord. The KoboldAI community is active, especially among creative writing users. No formal support.
13. Msty: Msty is a clean, simple app made for chatting with different models when you want to run LLM locally without a hassle.
Msty is a newer local AI app, and honestly, it’s been getting a lot of attention lately. And for good reason it just feels different. Most tools in this space look pretty rough around the edges. Msty actually looks good. It’s a desktop app that runs local models through Ollama, but you can also hook it up to OpenAI or Anthropic if you need to. Mix and match, totally up to you.
The interface is clean and easy to navigate. There’s also this “stacks” feature that lets you chain models together which is a pretty clever idea you don’t really see elsewhere.
Sure, it’s not packed with the most features on this list. But what it does have works really well. You can just tell the team thought hard about the experience.
If having a nice-looking, easy app for your local AI workflow matters to you give Msty a shot. It feels way more like real software than most free local LLM tools out there.
Key Features:
Clean, modern desktop UI — one of the best-designed interfaces in the local AI software space
Stacks feature — chain multiple AI models together for complex workflows
Supports local and remote models — Ollama, LM Studio, OpenAI, Anthropic — all in one app
Conversation management — organized, searchable history across all your chats
Customizable system prompts — set up different AI personas for different use cases
Prompt library — save and reuse prompts you use regularly
Pros & Cons
Pros & Cons
Pros
- Genuinely excellent UI design — feels like a product that's been thought through carefully
- Flexible model support makes it a great unified interface for mixed local/remote workflows
- Stacks feature is unique and useful for more complex tasks
- Regular updates with attention to user feedback
- Works great as a daily driver local AI assistant app
Cons
- Depends on external backends like Ollama for local models — not a standalone inference engine
- Some advanced features are still in development or behind paid tiers
- Smaller community than more established tools on this list
Device Compatibility:
- Windows and macOS currently. Linux support has been mentioned but wasn’t fully available at time of writing — check the official site for the latest.
Pricing:
- Free tier available with good core functionality. Paid plan for advanced features — current pricing on the Msty website. Reasonably priced for what it offers.
Customer Support:
Discord community and in-app feedback. Documentation available on the website. The team is responsive in Discord, which is nice to see.
14. Private LLM: Private LLM is a neat app built specifically for Macs and iPhones to help you run LLM locally and keep data safe.
Private LLM
100% on-device private AI for iPhone iPad and Mac with no internet required
Private LLM is made specifically for iPhone and Mac users who want AI that runs totally offline, no internet and no cloud. Nothing leaving your device. It’s built around Apple’s ecosystem and uses Apple Silicon’s neural engine to run models smoothly. So if you’ve got an M1, M2, or M3 Mac or a recent iPhone or iPad this thing just works.
And setup? There’s basically none. No config files, no messing with settings. You just open it and go. That’s kind of rare in the local AI space.
The app is clean and simple. It does one thing keeps your chats private. Everything stays on your device, full stop.
A lot of people are uncomfortable with how cloud AI apps handle their data. That’s exactly who this is built for. It’s pretty much a ChatGPT-style experience, but completely offline and totally in your control. Hard to argue with that.
Key Features:
100% on-device inference — models run on Apple Silicon with zero internet required
Optimized for Apple Neural Engine — faster and more power-efficient than CPU-only alternatives
Clean iOS and macOS UI — feels native to the Apple platform in the best way
Multiple model support — choose from several available models based on your device capabilities
iCloud sync optional — sync conversation history across devices if you choose, with no AI data leaving Apple’s ecosystem
Focus on privacy — designed explicitly as a private AI tool for personal use
Pros & Cons
Pros & Cons
Pros
- Best option for Apple users who want truly offline AI on iPhone and Mac
- No technical setup whatsoever — works like any regular iOS/macOS app
- Excellent performance on modern Apple Silicon chips
- Privacy-first design is genuinely built into the architecture, not bolted on
- Regular model updates from the developer
Cons
- Apple ecosystem only — no Android, no Windows, no Linux
- Paid app with no free tier — you pay upfront
- Model selection is more limited than desktop-focused tools with open model libraries
Device Compatibility:
- iPhone, iPad, and Mac running iOS 16+ / macOS 13+. Optimized for Apple Silicon. M-series chips give the best performance.
Pricing:
- Paid app available on the App Store and Mac App Store. Price is reasonable for a one-time purchase — check the App Store for the current price, as it can vary by region.
Customer Support:
App Store reviews and email support available. The developer is responsive to feedback. No community Discord or live chat.
15. Pinokio: Pinokio is a magical browser that lets you install and run LLM locally with just one click, no code needed.
Pinokio is kind of unlike anything else on this list. It’s not a model runner it’s more like an app store for AI tools. You open it up, browse through different AI apps and scripts, hit install, and it handles everything else. No messy setup, No weird errors, It just works.
Want Stable Diffusion? Click install. Want Text Generation WebUI? Click install. All the complicated stuff dependencies, environments, configs gets handled in the background automatically.
Think of it like a launcher that babysits all the hard parts for you. It’s super useful if you want to try out lots of different AI tools but don’t really want to become a Python expert first.
And yeah, Pinokio doesn’t run LLM locally by itself. But it makes installing and managing tools that do so much easier. That alone earns it a spot on this list especially for beginners just getting into offline AI tools.
Key Features:
One-click AI tool installation — installs and configures complex AI apps automatically
Curated app library — browse a growing catalog of AI tools, models, and scripts
Isolated environments — each app runs in its own space, avoiding dependency conflicts
Scriptable — power users can write Pinokio scripts to automate complex workflows
Works with Ollama, AUTOMATIC1111, and many more — broad compatibility with the open source AI ecosystem
Regular library updates — new AI tools get added to the catalog regularly
Pros & Cons
Pros & Cons
Pros
- Makes installing notoriously difficult AI tools genuinely simple — that's a real service
- Great for experimenting with different local AI tools without committing to complex setups
- Free to use — no subscription or payment required
- Isolated app environments mean less "it broke my Python setup" frustration
- Active community keeps adding new app scripts to the library
Cons
- It's a launcher, not a model runner — adds one more layer between you and running models
- The library of available apps depends on community contributions
- Can feel complex in its own right once you go beyond simple one-click installs
Device Compatibility:
- Windows and macOS supported. Linux support is available but the experience is smoothest on Windows and Mac. GPU requirements depend entirely on which apps you’re installing through it.
Pricing:
- Free to use. The apps it installs are also mostly free and open source. No paid tiers currently.
Customer Support:
Discord community, GitHub, and documentation on the official site. The community is active and helpful. No formal live support.
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