Free Alternatives: Run AI on Your Own Computer

You can run a capable AI chat model on your own computer for free, with no subscription and nothing leaving your machine, if it has enough memory and you accept slower, somewhat weaker answers than the best paid services give. The two easiest ways in are Ollama and LM Studio, both free to download. If you are weighing free plans against paid ones instead, see free vs paid AI chat and free vs paid AI creative tools.

What running AI yourself means

A chatbot website sends what you type to the company’s computers, which run the model and send the answer back. Running AI locally means you download the model itself, a large file of trained numbers, and a free program on your computer does the work.

Both tools in this guide say that local use stays on your machine. Ollama’s FAQ says: “Ollama runs locally. We don't see your prompts or data when you run locally.”Ollama, FAQ, read at source 22 Sep 2026: “Ollama runs locally. We don't see your prompts or data when you run locally.” LM Studio’s documentation says: “Nothing you enter into LM Studio when chatting with LLMs leaves your device.” It also says the app “can operate entirely offline, just make sure to get some model files first.”LM Studio, Offline Operation, read at source 23 Sep 2026: “Nothing you enter into LM Studio when chatting with LLMs leaves your device.”

Both companies also sell access to models that run on their own servers. Ollama’s setup says to “Sign in to use cloud models, or choose a local model.” LM Studio says “Cloud models require an LM Studio account with available credits”, while local models “can be used without an LM Studio account.”Ollama, Quickstart, read at source 22 Sep 2026: “Sign in to use cloud models, or choose a local model.” · LM Studio, Set Up Billing and Add Credits, read at source 23 Sep 2026: “Local and LM Link models do not use Bionic cloud credits, and can be used without an LM Studio account.” Ollama’s FAQ describes a local-only mode that turns its cloud features off.Ollama, FAQ, read at source 22 Sep 2026: “Ollama can run in local only mode by disabling Ollama's cloud features.”

Is your computer enough?

The limit is memory. The whole model has to be loaded into it, and LM Studio explains that “Loading a model typically means allocating memory to be able to accommodate the model's weights and other parameters in your computer's RAM.”LM Studio, Get started with LM Studio, read at source 23 Sep 2026: “Loading a model typically means allocating memory to be able to accommodate the model's weights and other parameters in your computer's RAM.”

LM Studio publishes the clearest minimums. On a Mac it needs Apple Silicon and says “16GB+ RAM recommended.” Smaller Macs may work: “You may still be able to use LM Studio on 8GB Macs, but stick to smaller models and modest context sizes.” Intel Macs are not supported. On Windows it recommends at least 16GB of RAM and “at least 4GB of dedicated VRAM”, which is memory on a separate graphics card.LM Studio, System Requirements, read at source 23 Sep 2026: “Intel-based Macs are currently not supported.” and, for Windows, “RAM: LLMs can consume a lot of RAM. At least 16GB of RAM is recommended.”

Ollama states operating systems rather than memory: Windows 10 22H2 or newer, and on a Mac “MacOS Sonoma (v14) or newer”, where Intel Macs run on the processor only. It also warns about disk space: the models “can be tens to hundreds of GB in size.”Ollama, Windows and macOS, both read at source 22 Sep 2026: “Windows 10 22H2 or newer, Home or Pro”; “Apple M series (CPU and GPU support) or x86 (CPU only)”.

For a sense of scale, Meta’s Muse Glimmer is sized for one high-end graphics card. Its model card lists the recommended compressed file as 16.8 GB and says it “fits 24 GB VRAM”. How that works is on how to run Muse Glimmer locally.Meta, Muse-Glimmer-30B-GGUF model card, read at source 22 Sep 2026: “Text model — start here, fits 24 GB VRAM”.

Ollama, step by step

Ollama is a small program that downloads and runs models. It has a desktop app, and you can also type short commands into a terminal.

1. Download it from ollama.com/download for macOS, Windows or Linux. The Windows installer does not need administrator rights. On Linux the documented command is curl -fsSL https://ollama.com/install.sh | sh.
2. Open the app, or type ollama in a terminal, and follow the setup prompts. Choose a local model, not a cloud one.
3. Run a model. Ollama’s own example is ollama run gemma4. The first time, this downloads the model, then opens a chat.
4. Stay local if you want to. Model names ending in :cloud run on Ollama’s servers, and cloud features can be switched off.

Ollama’s documentation gives these steps and commands; this page did not install it.Ollama, Quickstart, Linux, Windows and CLI Reference, all read at source 22 Sep 2026: “The Ollama install does not require Administrator, and installs in your home directory by default.” Ollama’s price page lists a free plan that includes “Run models locally”; paid plans add cloud use.Ollama, Pricing, read at source 23 Sep 2026: “Run models locally”.

LM Studio, step by step

LM Studio is a desktop app with a chat window and a built-in model search. Its download page now offers two apps: Bionic, an agent app, and the original LM Studio, described as “Experiment with LLMs on your computer. Chat interface and programmable API.” The steps below are for the original app.LM Studio, Download, read at source 23 Sep 2026: “Experiment with LLMs on your computer. Chat interface and programmable API.”

1. Install the latest version from lmstudio.ai/download, after checking the system requirements above.
2. Open the Discover tab and pick a model, or search for one by name.
3. Choose a download option. The Q in names like Q4 is quantisation, which LM Studio says “roughly means compressing model files in size, while giving up some degree of quality.” Its advice: “Choose a 4-bit option or higher if your machine is capable enough for running it.”
4. Go to the Chat tab, open the model loader, select the model, and start typing.

These steps are from LM Studio’s own guides; this page did not install it.LM Studio, Get started with LM Studio and Download an LLM, both read at source 23 Sep 2026: “Head over to the Discover tab to download models.” The free plan covers local use, and its terms allow use for “personal and / or internal business purposes”.LM Studio, Pricing and Terms of Use, both read at source 23 Sep 2026: “Can I use Bionic for free? Yes. The Free plan includes Bionic Agent and local model support.”

Which models to try

The table gives what each maker or tool page states. A download size is the file size on Ollama, not a measured memory need; you need at least that much memory, plus room to work.

Google, Gemma 4 model card and Gemma 4 announcement · Qwen, Qwen3.8-27B and Qwen-Image-2.1 model cards and Qwen Research License Agreement · Meta, Muse-Glimmer-30B-GGUF · DeepSeek, DeepSeek-V4.1-Flash · Black Forest Labs, FLUX.2 [klein] 4B · Ollama library pages for gemma4, qwen3.8, muse-glimmer and deepseek-v4.1-flash. All read at source 22 Sep 2026. Sizes and licences change; re-check the model card before relying on this.

Gemma 4. Google released it in April in four sizes; its model card now says “The models are available in five distinct sizes”, adding a 12B. The small E2B and E4B are “specifically designed for efficient local execution on laptops and mobile devices.” For the larger two, Google says “quantized versions run natively on consumer GPUs”. How it compares with Meta’s model is on Gemma 4 vs Muse Glimmer.Google, Gemma 4 model card and Gemma 4 announcement, both read at source 22 Sep 2026: “That's why Gemma 4 is released under a commercially permissive Apache 2.0 license.” The 12B repository was created on Hugging Face on 23 May 2026, per the Hugging Face API listing, read 23 Sep 2026: “google/gemma-4-12B-it 2026-05-23”.

Qwen3.8 has no small model yet. Qwen’s Hugging Face page lists three Qwen3.8 models, plus compressed FP8 copies of each, and the smallest is the 27B; the other two are far larger. The 27B is Apache 2.0, but the other two carry Qwen’s own licences, compared on AI labs outside the US.Hugging Face, API listing for Qwen3.8, read 23 Sep 2026: “Qwen/Qwen3.8-27B”, “Qwen/Qwen3.8-Flash-Next”, “Qwen/Qwen3.8-2.4T-A95B”. Qwen, Qwen3.8-Flash-Next model card, read at source 22 Sep 2026: “Number of Parameters: 125B with 6B activated”.

DeepSeek-V4.1-Flash is not a home model. Its weights are free under MIT, but it is “a multimodal Mixture-of-Experts (MoE) model with 552B backbone parameters”, and Ollama offers it only as a cloud model, which runs on Ollama’s servers.DeepSeek, DeepSeek-V4.1-Flash model card, read at source 22 Sep 2026: “This repository and the model weights are licensed under the MIT License.” · Ollama, deepseek-v4.1-flash, read at source 22 Sep 2026: “ollama run deepseek-v4.1-flash:cloud”.

Images need a different tool. The model pages for the two image models give Diffusers, a programming library, as the way to run them, and FLUX.2 [klein] 4B is also in ComfyUI, a node-based image app. Neither is covered by Ollama’s or LM Studio’s guides read here, so expect more setup. FLUX.2 [klein] 4B “Runs on consumer GPUs (~13GB VRAM).” and its card says: “Open weights available for commercial use under the Apache 2.0 license.”Black Forest Labs, FLUX.2 [klein] 4B model card, read at source 22 Sep 2026: “Runs on consumer GPUs (~13GB VRAM).” Other FLUX models are not free for business use; see which image model.

Qwen-Image-2.1 is for research only. Its card says “We are excited to open-source” it, but the licence next to the weights grants rights “FOR NON-COMMERCIAL PURPOSES ONLY”, and defines that as “for research or evaluation purposes only.” Commercial use needs a separate licence from the maker.Qwen, Qwen-Image-2.1 model card and Qwen Research License Agreement, both read at source 22 Sep 2026: “You shall not use the Materials for any commercial purpose without obtaining a separate commercial license from us.” That is the gap between open weights and open source, covered on AI terms people get wrong and open or closed. LM Studio’s terms say the same in general: models you download come under their makers’ licences, not LM Studio’s.LM Studio, Terms of Use, read at source 23 Sep 2026: “SUCH THIRD PARTY PRODUCTS ARE MADE AVAILABLE TO YOU PURSUANT TO A LICENSE AGREEMENT BETWEEN YOU AND THE THIRD PARTY PROVIDER”.

What you give up

• Quality at the top end. The models that fit at home are smaller than the ones behind paid services. For drafting and summarising the gap may not matter; for hard reasoning it can. The evidence is weighed on local or cloud.
• Speed. It depends on your hardware, and the bigger the model, the more it asks of it. Nothing was timed for this page.
• Setup and upkeep. You choose the model, update it and fix it when it breaks; that becomes your job.
• Hardware and electricity. The model is free, but the computer is not. If you would have to buy a graphics card, compare its cost with a year of a paid plan; long sessions also use your electricity.
• Safety features. A provider’s filters and monitoring run on its servers and do not come with the downloaded file; see open or closed.

What you get back is concrete: no monthly fee, no ads, answers that work without the internet, and a model that cannot be changed or withdrawn by its maker once it is on your disk.Reasoning, September 2026 — follows from the tools’ offline and local-use statements quoted above; no cost or energy figure was found in a primary source, so none is given.

What this page could not verify

• How much memory most models really use. Of the models in the table, only Meta and Black Forest Labs state a figure for home hardware. The download sizes in the table are Ollama’s, and actual use is higher with long chats.
• Speed on any computer. Nothing was installed or timed for this page.
• Quality. Every model card compares itself with rivals; none of those scores was checked, and this page ranks nothing.
• Electricity cost. None of the pages read here gives one.
• Whether the free plans stay free. Both tools’ price pages were read on 23 Sep 2026 and can change.