Yes—you can run an AI assistant on your computer using a locally stored model, but “local” does not automatically mean every feature is private or works offline. The model can answer prompts on your device while optional cloud models, document tools, embeddings, voice services, or web features send data elsewhere. Check the destination for each part of the assistant, not just the app’s name.
What makes an AI assistant local?
A local assistant needs an interface, a runtime that loads a model, and model files stored on your computer. For example, LM Studio describes downloading a model, loading it into memory, and chatting with it. Model weights and other parameters use computer memory; the model and context you choose affect whether they fit. See LM Studio’s explanation of loading models.
Another option is to use an interface such as Open WebUI with a local model server, including Ollama or llama.cpp. The interface and the model server are separate parts of the setup, so installing a chat interface alone does not mean a local model is configured.
Does a local assistant keep your data private?
It can keep prompts and responses on your computer when inference uses a local model server, but privacy depends on where each operation sends data. Open WebUI says the selected provider endpoint determines where inference happens: a cloud model receives the prompt and included context, while a local endpoint runs the model on the selected server. Its documentation also cautions that configured cloud tools, document extraction, or embedding services may be remote even when inference is local. Review the providers configured for retrieval, embeddings, document processing, web access, and voice before using sensitive material. Open WebUI’s quick-start documentation describes its connection options.
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Ollama’s privacy policy says: “We do not collect, store, transmit, or have access to your prompts, responses, model interactions, or other content you process locally.” That statement concerns content processed locally with Ollama; it does not cover other software you connect or cloud-hosted models. The same policy says Ollama may collect limited device and usage metadata and processes prompts and responses sent to its cloud-hosted models transiently. Read the Ollama privacy policy for its full scope.
Can you use one offline?
LM Studio says that once a model is downloaded, it runs locally and can be used entirely offline. Its documentation says chat entries and document processing for its retrieval-augmented generation (RAG) workflow remain on-device. However, you need an internet connection to search its model catalog, download models or runtimes, and check for application updates. In other words, offline inference is possible after setup; discovery, downloads, and updates are separate tasks that may need connectivity. See LM Studio’s offline-use documentation.
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Other assistants may have different requirements. Open WebUI supports local model servers and hosted providers, and some document, retrieval, and voice features require additional providers or components. Its quick-start guide documents a Docker installation, while its documentation describes configurable integrations. Check the exact components you plan to use rather than assuming the whole workflow stays offline.
What computer do you need?
There is no universal minimum in the cited guidance: hardware needs depend on the software, model, and context size. LM Studio’s current system requirements list Apple Silicon M1, M2, M3, or M4 with macOS 14 or newer. For that configuration, it recommends 16 GB or more of RAM; an 8 GB Mac may still work with smaller models and modest context sizes. These are LM Studio’s recommendations for the listed Mac setup, not a guarantee for every model or a requirement for all local AI software. Check LM Studio’s current system requirements before installing.
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When choosing a model, allow for memory used by both its weights and other parameters. A smaller model or shorter context may fit where a larger model does not. The useful question is whether your computer can run the model and features you need—not whether it carries a generic “AI PC” label.
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- Desktop-first setup: LM Studio provides an application for finding and loading models. Its documented offline behavior applies after the model and required software are downloaded.
- Flexible interface: Open WebUI can connect to a local model server or a hosted provider. This offers configuration choices, but each connection and optional service needs its own privacy check.
- Local model runtime: Ollama is one option for running models locally; its privacy statement applies to locally processed content, not automatically to other connected tools or cloud models.
Before settling on a setup, check four things: where inference runs, whether the model fits your hardware, which functions work offline, and which providers receive data for connected features. The cited product documentation does not establish comparative speed, response quality, or performance on a particular computer, so those should not be assumed from these descriptions.
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