Run DeepSeek R1 Locally: A Full Guide & My Honest Review of this Free OpenAI Alternative (2025)

Have you heard the buzz about DeepSeek R1? I recently stumbled upon this new open-source AI model, and honestly, I’m pretty excited about it. Why? Because DeepSeek R1 is making waves by going toe-to-toe with some of the biggest names in AI, like OpenAI’s o1 and Claude 3.5 Sonnet, especially when it comes to math, coding, and logical thinking. People online are already comparing DeepSeek R1 to OpenAI o1 and Claude 3.5 Sonnet, and from my own testing using ollama and chatbox ,the hype seems real. It’s seriously impressive. But the absolute best part? You can run DeepSeek R1 locally on your own computer. That means total privacy and it’s 100% free!

I got it up and running on my machine and have been playing around with it. Let me tell you, the setup is surprisingly easy. So easy, in fact, that I wanted to share a quick guide with you, along with my personal review of how it performs. Whether you’re on a Mac, Windows, or Linux, this guide will work for you. Let’s dive in!

What is DeepSeek R1 and Why the Hype?

So, what exactly is DeepSeek R1, and why is everyone talking about it? Simply put, DeepSeek R1 is a brand-new open-source AI model that’s been turning heads in the AI world. It’s designed to be incredibly capable, and early benchmarks show it holding its own against some of the top-tier models out there, including those from OpenAI and Claude.

Think about it, an open-source AI model that can compete with industry giants! That’s a big deal. The online chatter is full of comparisons and excitement, and for good reason. While it’s mentioned as a “distilled model,” meaning it’s a more compact and efficient version, its performance is still remarkably impressive. It’s bringing powerful AI capabilities to more people, and that’s something to be genuinely excited about.

The Power of Local AI: Why Run DeepSeek R1 on Your Machine?

Why bother running DeepSeek R1 locally when there are cloud-based AI options out there? Well, the benefits are significant, especially if you value privacy and cost-effectiveness.

First and foremost, privacy is a huge win. When you run R1 locally, all your interactions and data stay right on your computer. You’re not sending your prompts and conversations to external servers, which gives you much more control over your information.

Secondly, it’s completely free to use after the initial setup. No subscription fees, no usage-based charges once you have it running, you’re good to go. This is a massive advantage compared to cloud AI services that often come with recurring costs.

Finally, you can even use DeepSeek R1 offline. No internet connection? No problem. As long as you have it set up, you can access its capabilities anytime, anywhere. For anyone concerned about data privacy or tired of subscription costs, running a local AI model is a fantastic option.

Understanding DeepSeek R1 Model Sizes: Choosing the Right One for You

One thing to know about DeepSeek R1 is that it comes in different sizes, ranging from a 1.5B (billion parameter) version all the way up to a massive 70B version. Think of parameters as the “size” or complexity of the AI model – generally, more parameters mean a smarter and more capable model.

Here’s a quick rundown of the DeepSeek R1 model sizes available on Ollama, the tool we’ll use to run it:

• 1.5B version: The smallest and lightest, great for testing or machines with limited resources.
• 8B version: A good balance of performance and resource usage, a solid starting point for most users.
• 14B version: Stepping up in capability, offering improved performance for more demanding tasks.
• 32B version: Getting into the larger, more powerful models, requiring more GPU power.
• 70B version: The largest and most intelligent, designed for top-tier performance but needs significant GPU resources.

Choosing the right size depends on your computer’s hardware. If you’re just starting out, I highly recommend beginning with the 8B model. It’s a great way to test the waters and see how it performs without needing a super powerful machine. You can always try larger models later if your system can handle it and you want even more performance.

Step-by-Step Guide: Running DeepSeek R1 Locally – Easy Setup

Alright, let’s get to the fun part, Don’t worry, it’s much easier than you might think. We’re going to use two main tools: Ollama to manage and run the model, and Chatbox for a user-friendly interface to chat.

Step 1: Install Ollama – Your Local AI Model Manager

First, you need to install Ollama. Think of Ollama as the engine that will run the DeepSeek model on your computer. It makes managing and running AI models locally incredibly straightforward.

Head over to the Ollama website and download the version for your operating system (Mac, Windows, or Linux). The installation process is simple – just follow the on-screen instructions.

Step 2: Pull and Run the DeepSeek R1 Model with Ollama

Once Ollama is installed, running DeepSeek R1 is just a single command away! Open up your computer’s terminal (or command prompt on Windows). To download and run the 8B model (my recommended starting point), simply type in the following command and press Enter:

 ollama run deepseek-r1:8b 

Ollama will automatically download the DeepSeek R1 8B model and then start running it locally on your machine. You’ll see it downloading in the terminal. Once it’s done, the model will be ready to go.

If you want to try a different size model (like the 1.5B, 14B, 32B, or 70B versions), just replace :8b in the command with the desired size, for example: ollama run deepseek-r1:70b for the 70B model. Remember to start with the 8B version to get a feel for it first.

Step 3: Set Up Chatbox – A User-Friendly Interface

Now that DeepSeek R1 is running in the background thanks to Ollama, we need a nice way to chat with it. That’s where Chatbox comes in. Chatbox is a free, clean, and powerful desktop application designed to work with various AI models, including Ollama. It provides a user-friendly interface for interacting with your local AI model. Plus, it’s focused on privacy, keeping all your data local.

Download Chatbox from their website.

Step 4: Configure Chatbox to Connect to Your Local DeepSeek R1

With Chatbox installed and DeepSeek R1 running via Ollama, we just need to connect them. Open Chatbox and go to the settings menu. Look for the “Model Provider” setting and switch it to “Ollama”.

You’ll likely see options for cloud AI models within Chatbox, but since we’re running DeepSeek R1 locally, we can ignore those – no license keys or payments needed!

Next, you’ll need to set the Ollama API host. The default setting in Chatbox is usually http://127.0.0.1:11434, and this should work perfectly right out of the box. This address points to where Ollama is running on your local machine.

Finally, in Chatbox, you should be able to select the DeepSeek R1 model you downloaded (like deepseek-r1:8b) from the model list. Choose it, hit save, and that’s it! You are now all set to chat with DeepSeek R1 running directly on your computer!

Review and Performance Tests of Local R1

Okay, so setup is done but how does DeepSeek R1 actually perform? I’ve been testing the DeepSeek R1 8B model running locally using Chatbox, and I have to say, I’m genuinely impressed. Chatbox’s interface is clean and easy to use, and I especially like its artifact preview feature, which is handy for things like code generation.

Here are a couple of quick tests I ran:

Test 1: Explain TCP

I asked DeepSeek R1: “Explain TCP”. The response I got was surprisingly detailed and accurate, especially considering it’s just the 8B model. It provided a clear and concise explanation of TCP, hitting the key points.

Test 2: Make a Pac-Man Game

Next, I tried something a bit more complex: “Make a Pac-Man game”. DeepSeek R1 generated code for a basic Pac-Man game! While I couldn’t immediately play it without some tweaking (and to be transparent, for this particular test, I briefly used a cloud model due to resource constraints on my machine for the largest models), the code itself was quite impressive for a quick generation. It showed a good understanding of game logic and structure.

Overall, my experience with local DeepSeek R1 has been very positive. It’s not a perfect, magic replacement for the top-tier cloud models, but it’s surprisingly capable for something that runs locally and is completely free. The fact that it works offline and keeps my data private is a huge bonus.

DeepSeek R1 vs. OpenAI and Claude: Is it a Real Alternative?

Let’s address the big question: Is DeepSeek R1 a real alternative to models from OpenAI and Claude? In many ways, yes, it is.

DeepSeek R1 shines in several key areas:

• It’s Free: Completely free to use after setup, unlike subscription-based services.
• It’s Local and Private: Your data stays on your machine, offering superior privacy.
• Impressive Performance: Especially for an open-source AI model of its size, it performs remarkably well in tasks like coding, math, and reasoning, often comparable to much larger models.

However, it’s important to be realistic. While DeepSeek R1 is excellent, especially the 8B model I tested, it might not outperform the absolute top-of-the-line, massive cloud models from OpenAI or Claude in every single complex task. There might be subtle differences in nuanced understanding or handling extremely intricate prompts.

That being said, for a vast majority of users and use cases, DeepSeek R1 offers a fantastic balance of performance, accessibility, and privacy. It’s not a “magic replacement,” but it’s an incredibly strong and viable alternative, especially if you prioritize local execution and cost savings. The online community’s positive feedback and comparisons further reinforce this point.

Conclusion: Embrace Local AI

DeepSeek R1 is a game-changer in the world of local AI models. It brings powerful AI capabilities directly to your computer, offering a compelling alternative to cloud-based services with the added benefits of privacy and zero cost after setup. The ease of setup using Ollama and Chatbox makes it accessible to anyone, regardless of their technical expertise.

If you’re curious about exploring local AI, I highly encourage you to try running DeepSeek R1 locally. It’s a fantastic way to experience the power of advanced AI in a private and cost-effective way. The performance is genuinely impressive, and the potential applications are vast. The future of AI is becoming more accessible, and DeepSeek R1 is leading the charge.

Ready to try it out? Follow the steps in this guide and get DeepSeek R1 running on your machine today! Let me know in the comments below about your experiences and what you think of DeepSeek R1. What will you use your local AI model for? I’m eager to hear your thoughts!

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