In this guide, we’ll walk you through how to install ollama and run deepseek, adding different models, and understanding what each model offers—including DeepSeek R1 and others.

A Complete Guide to Ollama: Installation, Models, and Usage

Ollama is a powerful tool that simplifies the process of running and managing large language models locally. Whether you’re a developer looking for AI-assisted coding or a researcher exploring natural language processing, Ollama provides an intuitive way to work with various models.

How to install ollama and run deepseek:

Installing Ollama on macOS, Linux, and Windows

Ollama is easy to install on multiple platforms. Follow the steps below to get started.

macOS & Linux Installation

Open a terminal.
Run the following command:curl -fsSL https://ollama.ai/install.sh | sh
Restart your terminal and verify the installation by running:ollama --version

Windows Installation

Download the installer from Ollama’s official website.
Run the installer and follow the setup instructions.
Once installed, open a command prompt and verify the installation with:ollama --version

Using Ollama

Once installed, Ollama provides an easy way to run and manage models with a simple command-line interface.

Running a Model

To run a model, use:

ollama run <model-name>

For example, to run mistral, use:

ollama run mistral

Listing Available Models

To check the models installed on your machine:

ollama list

Pulling a New Model

To download a new model from the registry:

ollama pull <model-name>

For example, to download DeepSeek R1:

ollama pull deepseek-r1

Available Models and Their Features

Ollama supports various AI models optimized for different tasks. Below are some popular ones for how to install ollama and run deepseek:

1. Mistral

Size: 7B parameters
Type: General-purpose LLM
Use case: Coding, writing, chat applications

2. DeepSeek R1

Size: 67B parameters
Type: Code-focused language model
Use case: AI-assisted programming, code generation
How to add: ollama pull deepseek-r1

3. Llama 2

Size: Available in 7B, 13B, and 70B parameters
Type: Open-source LLM from Meta
Use case: Conversational AI, creative writing
How to add: ollama pull llama2

4. Gemma

Size: 2B, 7B parameters
Type: Lightweight model by Google DeepMind
Use case: Low-resource devices, fast inference
How to add: ollama pull gemma

Managing Models

If you no longer need a model, you can remove it using:

ollama rm <model-name>

To update a model to the latest version:

ollama pull <model-name>