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What “running an AI model locally” means
In local inference, the model runs on your computer and handles prompts there. The model files must already be on the device; finding and downloading them require an internet connection. After download, LM Studio says local chat, document work, and local-server inference can work without internet access. Its documentation puts it this way: “Once you have an LLM onto your machine, the model will run locally and you should be good to go entirely offline.” LM Studio’s offline documentation
Use “open-weight” unless the specific model’s license justifies calling it open source. A model’s availability for download does not, by itself, establish that its license meets the open-source definition.
Choose a local runtime
Two practical starting points are LM Studio and Ollama. They support different workflows, and the available documentation does not establish a controlled performance comparison or a universal winner.
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| Runtime | Documented workflow | Privacy controls and considerations |
|---|---|---|
| LM Studio | Graphical model discovery and chat, local document/RAG work, and a local inference server. | Local chat and document processing can work offline after the model is downloaded. Searching for and downloading models, and checking for software updates, use the internet. LM Studio offline documentation and LM Studio privacy policy |
| Ollama | Local model runtime and server, with model files stored on the computer. | Ollama documents a local-only setting that disables cloud models and web search. It binds to localhost by default; changing the bind address can expose the server to a network. Ollama FAQ and Ollama cloud configuration documentation |
Before installing either runtime, check its current official system requirements and confirm that the model you want is supported. Also review the model’s format, license, and memory guidance. Requirements vary, so there is no single RAM, VRAM, or model-size threshold that applies to every computer.
Set up and verify a local model
- Install a runtime. Choose LM Studio for its documented graphical workflow, or Ollama if you want its local server and configuration options. Follow the current installation instructions for your operating system on the tool’s official site.
- Check model compatibility. Select a model whose format is supported by your runtime, and check the model publisher’s license and hardware guidance.
- Download the model while online. Model search and downloads need network access. LM Studio also documents sideloading models obtained outside the app; use the runtime’s current instructions for importing them.
- Start a basic local chat. Load the downloaded model and send a simple prompt. If your intended task is document question-answering, test that workflow separately; document/RAG support is not the same as using an online search service.
- Set the privacy boundary. Select a local model and disable cloud models or web search when you do not want prompts sent to remote services. Avoid exposing a local server to your network unless you understand who can reach it and how it is secured.
- Test offline behavior if you need it. After the model and runtime are installed, disconnect from the internet and try the exact workflow you plan to use. This checks whether that workflow works offline; it is not a security audit or proof that the application makes no other network requests.
What stays on the device—and what may leave it
Privacy depends on the feature and settings in use. LM Studio says local messages, histories, and documents are not transmitted, while its policy also describes network requests for model searches and downloads and software-update checks. Cloud models and web search send requests to remote services for processing. LM Studio privacy policy
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Ollama says prompts and responses processed locally are not collected, stored, transmitted, or accessible to Ollama. Its policy separately describes limited device and usage metadata, and says cloud-hosted models process prompts and responses transiently. Ollama’s local-only configuration disables cloud models and web search. Ollama privacy policy and Ollama FAQ
- Local inference: With a downloaded model and local inference enabled, prompts can be processed on your computer.
- Downloads and updates: These may require internet access even if you use the model offline afterward.
- Cloud models and web search: These can route prompts or search requests to remote services.
- Remote access: A server made reachable beyond your computer creates a different access boundary from a local-only setup.
Do not treat an “offline” label as a blanket privacy guarantee. Check which model and features are active, and verify the behavior you rely on.
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Fit the model to your memory and storage
Available memory is a practical constraint. Ollama notes that CPU inference is constrained by available system memory and GPU inference by available VRAM. Longer context and parallel requests add memory demand, so a model that loads for a short, single prompt may not work as well for a long conversation or multiple concurrent tasks. Consult the selected model’s guidance and leave room for the workload you intend to run. Ollama FAQ
Model files also occupy disk space. Ollama stores them locally by default and documents an environment variable for choosing a different storage directory. If internal storage is limited, an external SSD is one optional place to keep model files; it is not required, and there is no universal capacity recommendation. Ollama FAQ
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Keep a local server local
A local runtime may provide a server for applications on your computer. Ollama binds to localhost by default; changing its bind address can make the server reachable over a network. Do not change that setting or add a tunnel or other remote-access path unless you intend to permit access and have considered authentication and network security. Ollama FAQ
For sensitive work, use a downloaded local model, turn off cloud and web-search features, and avoid remote access. Test the precise workflow offline if offline operation is a requirement.
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