Free OpenAI o1 Alternative That Runs Locally?
I recently discovered DeepSeek R1, and I have to say—I’m seriously impressed. It’s an open-source AI model that competes with OpenAI’s o1 and Claude 3.5 Sonnet in math, coding, and reasoning tasks. And the best part? You can run it locally, for free!
If you're looking for a powerful AI model without cloud dependencies or privacy concerns, DeepSeek R1 is a fantastic option. I've got it running on my machine, and here’s how you can set it up too.
Step 1: Install Ollama
Ollama is an AI model runner that lets you run large language models locally. Download and install it for your OS (Mac, Windows, or Linux).
Once installed, open a terminal and verify it's working by running:
type ollama
Step 2: Pull and Run the DeepSeek R1 Model
Ollama offers different model sizes. Choose the one that best suits your system:
1.5B version (smallest):
ollama run deepseek-r1:1.5b
8B version:
ollama run deepseek-r1:8b
14B version:
ollama run deepseek-r1:14b
32B version:
ollama run deepseek-r1:32b
70B version (biggest & smartest):
ollama run deepseek-r1:70b
💡 Tip: Start with a smaller model first to test performance. The 32B and 70B versions require serious GPU power, so ensure your hardware can handle them.
Step 3: Set Up Chatbox for a Better AI Interface
Chatbox is a free, privacy-focused AI chat client that supports locally running models. Here’s how to configure it:
Download and install Chatbox.
Open settings and switch the model provider to Ollama.
Set the API host to:
http://127.0.0.1:11434
Select DeepSeek R1 and hit save.
That’s it! You can now chat with DeepSeek R1 running entirely on your machine—no cloud, no cost, full privacy!
Performance Review & Test Results
Here are some tests I ran using the DeepSeek R1 8B model:
- Explain TCP
The response was solid, demonstrating clear reasoning and technical accuracy. For an 8B model, it’s impressive!
- Generate a Pac-Man Game
DeepSeek R1 generated functional code, but there were minor bugs that needed tweaking. I suspect the larger 70B model would perform even better.
💡 Note: I ran this test using a cloud-hosted DeepSeek R1 model since my Mac lacks the space for the 70B version.
Final Thoughts
✅ Pros:
- Completely free & runs locally
- Matches OpenAI o1 & Claude 3.5 Sonnet in many tasks
- Privacy-focused (no cloud dependency)
- Scalable from 1.5B to 70B models
❌ Cons:
- Larger models require powerful GPUs
- Some minor bugs in generated code
Overall, DeepSeek R1 is an incredible local AI model. If you care about privacy and performance, give it a try! 🚀
Let me know if you have any questions or run into issues. Happy coding!
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