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How to Install Ollama and Run Your First Local Language Model

Install Ollama and use one command to download and chat with a first local model on macOS, Windows, or Linux.
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Install Ollama from its official download page, then run ollama run gemma4:e2b in a terminal to download a starter model and open an interactive local chat. This walkthrough covers macOS, Windows, and Linux; the command-line example runs the model on your computer rather than using Ollama’s hosted cloud models.

What you need to know before installing Ollama

Ollama supports both local models and cloud models. The steps below use a local model, so the Quickstart chat does not require an API key. Cloud use is a separate workflow and may require sign-in or an API key; do not assume every Ollama model runs on your computer.

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Model requirements vary. For the Quickstart’s Gemma 4 E2B example, Ollama lists a download of about 7.2 GB and recommends 8 GB of available VRAM, or unified memory on a Mac. These figures apply to that example, not to every Ollama model. Larger context windows need more memory, and the Quickstart notes that system RAM fallback can allow the example to run with slower responses.

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How to install Ollama on macOS, Windows, or Linux

Get the installer from the official Ollama download page and follow the instructions for your operating system. The available installer route and minimum OS requirements can change, so check the page before installing. At the time of the current Ollama documentation, the macOS page specifies macOS 14 Sonoma or later, and the Windows page specifies Windows 10 or later.

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macOS

Use the macOS download on Ollama’s page. The page also provides this Terminal command for macOS and Linux:

curl -fsSL https://ollama.com/install.sh | sh

Open Ollama after installation. Do not use this shell command in Windows PowerShell.

Windows

Use the Windows download from Ollama’s page. Its PowerShell installation command is:

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irm https://ollama.com/install.ps1 | iex

Run that command in PowerShell, not in a macOS or Linux terminal. The Windows download page currently states Windows 10 or later.

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Linux

Use the Linux installation instructions on Ollama’s official download page. The page currently shows the same shell command listed for macOS:

curl -fsSL https://ollama.com/install.sh | sh

Run your first local model

  1. Install and open Ollama for your operating system.

  2. Open a terminal (or PowerShell on Windows) and run ollama run gemma4:e2b.

  3. Wait while Ollama downloads the model. The first run needs to retrieve its model files before the chat begins.

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  4. When the interactive prompt appears, type a message to chat. Enter /bye to exit.

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This is the direct chat-first route in Ollama’s Quickstart. You do not need to make an API request to try the model.

Use the Ollama desktop app instead (optional)

Ollama also offers a desktop app for macOS and Windows. The app can download models and provide a chat interface; Ollama’s July 30, 2025 announcement also described dragging files into a chat. Choose the app if you prefer a graphical interface, or use the terminal command above as a concise, repeatable first-run example. The cited app announcement covers macOS and Windows, not Linux.

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Check hardware compatibility and diagnose a slow run

Local inference depends on the model, available memory, GPU, operating system, and supported drivers or backend. Ollama documents NVIDIA, AMD, Apple Metal, and Vulkan GPU paths, with platform and driver qualifications. Its current hardware documentation lists NVIDIA compute capability 5.0+ and driver 550+, with driver 570+ for compute capabilities 5.0–6.2; AMD support depends on ROCm and platform, Metal is the Apple GPU path, and Vulkan provides additional Windows/Linux GPU options. Check the live Ollama hardware support page for the current compatibility details rather than assuming a GPU will accelerate every setup.

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  • If the model responds slowly, performance may be limited by available memory or hardware. The Quickstart says RAM fallback can make responses slower.

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  • Check whether your GPU family, operating system, and driver or backend are listed as supported.

  • If memory is tight, try a model or context size suited to your machine. Requirements are model-specific; the Gemma 4 E2B figures above are not universal Ollama minimums.

Model files use disk space, but storage is not inference memory: an external SSD can store downloads, yet it does not replace VRAM or Mac unified memory.

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Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.

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