Discover How to Use Coding Assistants for Free on RTX AI PCs

Coding has always been about problem-solving—but let’s be honest, a big part of it is also digging through docs, setting up boilerplate code, and fixing those bugs that just won’t go away. That’s where AI coding assistants—often called AI copilots—step in.

Think of them as your virtual sidekicks. They suggest code, explain functions, debug errors, and handle repetitive work so you can stay focused on the creative side of development. Whether you’re a seasoned engineer or just starting out, these tools can take a lot of weight off your shoulders.

But here’s the real question: How do they actually work—and do you need a subscription to use them?

Cloud vs. Local: Two Ways to Run Coding Assistants

Most modern IDEs like Visual Studio Code and PyCharm already support AI-driven features. You can run these assistants in two main ways:

1. Cloud-Based

• Your code is sent to servers somewhere out on the internet.

• You get suggestions back from large AI models hosted in the cloud.

• Upside: You don’t need powerful hardware.

• Downside: It can be slower, and sending sensitive code online might not always feel secure.

2. Local (On Your Own PC)

• Everything runs directly on your machine—fast, private, and secure.

• No sending code to the cloud, no usage tracking, and no recurring subscription fees.

• All you need is the right hardware—and that’s where NVIDIA GeForce RTX GPUs shine.

With RTX AI PCs, your computer has the horsepower to run advanced AI models smoothly. That means instant suggestions, offline privacy, and zero extra costs if you already own the GPU.

Tools to Get Started on Your RTX AI PC

Here are some powerful tools you can try right now:

• Continue.dev – An open-source extension for VS Code. Integrates with Ollama and others, offering autocomplete, chat, and in-editor AI tutoring.

• Tabby – A cross-platform tool powered by RTX GPUs. Great for code completion, inline chats, and handling quirky queries.

• OpenInterpreter – Still evolving, but already super useful for DevOps and command-line automation.

• LM Studio – A playground for experimenting with AI models and interactive coding.

• Ollama – Perfect for running models like Code Llama locally with full control.

These tools are optimized for RTX PRO GPUs, giving developers a seamless, efficient experience without relying on external servers.

Why This Matters for Developers, Students, and Hobbyists

The beauty of running coding assistants locally is freedom. Whether you’re a professional developer handling sensitive projects, a student learning the ropes, or a hobbyist experimenting with generative AI, an RTX AI PC gives you all-in-one flexibility.

• Developers: Build faster, debug smarter, and keep your projects secure.

• Students: Learn coding with real-time support and hands-on AI tools.

• Hobbyists: Explore AI, gaming, and coding projects on one system.

NVIDIA is even encouraging creativity with initiatives like the Plug and Play: Project G-Assist Plug-In Hackathon, where developers push the limits of what’s possible with RTX-powered AI tools.

Coding assistants aren’t here to replace you—they’re here to work with you. With the power of RTX AI PCs, you can keep your workflow private, cut through repetitive tasks, and focus on what matters: solving problems and building things that last.

So gear up, fire up your RTX AI PC, and let your AI copilots turn coding into a faster, smarter, and more exciting experience.

Let’s code smarter, not harder.