We’re in the middle of an AI revolution, and while the new technology’s benefits are clear, figuring out where to get started can be confusing. You’re faced with buzzwords and lingo, and a nonstop stream of AI-related news makes it difficult to resolve how AI applies to you.
But here’s the good news: GeForce’s RTX 50 Series GPUs serve as a great hardware platform to explore generative AI right on your own PC. From running large language models to playing AI-enhanced games, RTX 50 GPUs make generative AI more accessible than ever before.
Follow along as we explain Generative AI, show you how it’s being used to transform science, and then help you get started with AI on your GeForce RTX 50 Series powered PC.
What is Generative AI?
Generative AI has become an umbrella term for various AI technologies. When you type a prompt into your AI engine of choice, a bunch of highly specialized AI programs called “models” spring into action.
These models individually excel at specific tasks, such as recognizing patterns in language, images, audio, computer code, and more. But they can also work together to solve more complicated problems. The models typically run on enormous computers in data centers, though that’s changing with PC hardware running GeForce RTX 50 Series graphics cards.
The models excel in breaking up problems into individual components, and then work together to generate helpful results. In effect, each model handles a portion of the problem they’re trained for, then passes that output to other models.
In fact, our brains handle these types of complicated cognitive tasks without any conscious thought at all. And now, with Generative AI running locally on PC hardware, these scenarios—once limited to human brain power—enter the realm of what’s possible on a computer.
Most generative AI starts with a large language model, or LLM, which understands normal written language. When you type a prompt for an LLM, the model parses it for meaning and then can pass that output to any number of other models—and there are models that generate images, audio, spoken voice, software code, and more.
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What does adding an NVIDIA GPU to your PC get you?
Generative AI represents an enormous technological shift, and it’s already having an impact on a variety of industries.
Programmers are using generative AI to write better code, faster than they were able to before. Drug companies are using AI to develop new treatments for diseases—treatments that are more effective or have fewer side effects.
And getting value out of generative AI isn’t limited to scientific breakthroughs. It can also summarize meetings, parse complicated datasets, generate your grocery list using your family’s favorite recipes, or just improve your PC gaming frame rates.
Bottom line: AI can help you get you more done in less time than what’s been possible with traditional software. And running generative AI models locally on your PC offers a few big advantages: costs are relatively fixed, processing is generally faster compared to cloud-based AI, and if you’re concerned about security, running AI locally means you don’t have to upload proprietary data to someone else’s servers.
Unlimited access to cloud AI models can cost $200 or more each month. That quickly gets expensive. But once you’ve bought (or built) a machine with a GeForce 50 Series GPU that’s capable of running AI locally, you’re really only paying for the electricity your machine consumes.
But GeForce RTX 50 Series GPUs offer even more benefits: raw speed. When you use one of the massive cloud-based AI services, you’re sharing compute time with millions of other users. On the other hands, when you’re running locally on a GPU you own, you don’t have to wait in line for your next prompt.
And the security benefits can’t be over-emphasized. Many of the free—and even some paid—cloud-based AI services train their models on prompts that users input. That means if you upload proprietary data as part of an online prompt, it can show up in later versions of the model.
You just bought an RTX 50 series GPU. What’s next?
Downloading and running generative AI models locally used to be difficult, but now there are tools that make it much more accessible. One of our favorites is Ollama, which makes it easy to run popular open models locally on your own PC, and take full advantage of your GeForce RTX 50 Series GPU.
To get started, grab the latest version of Ollama from the download page and install it on your PC. Once it’s installed, open a Terminal window and type ollama run llama3.2. This will download one of Meta’s smaller Llama LLMs and let you start chatting with it and experimenting with prompts. When you’re done, or want to try another model, just type /bye at the prompt.
The Ollama site maintains a list of all the different models that are available. We recommend checking out one of the new reasoning models, like deepseek-r1, which walk you through the thought processes behind their responses to your prompts. The models in Ollama are all free to download, but some of them are quite large.
If you want to try out AI image generation running locally on your GeForce RTX 50 Series cards, you’ll want to try Stable Diffusion. Make sure to watch this 5-minute tutorial video, which will help guide you through the process.
Once you’re done experimenting with text and image generation, you can fire up one of the 75-plus games that support DLSS 4. DLSS is NVIDIA’s suite of AI tools, which enable high-refresh rate 4K gaming, even in the most advanced ray-tracing games. Using DLSS Multi Frame Generation and the new transformer AI upscaling model lets your GeForce RTX 50 Series card get up to 8X the performance of traditional brute-force rendering. PCWorld has published an explainer on DLSS 4, and all the benefits it provides to PC gamers.
Between running local LLMs, creating AI art, and playing DLSS 4 games, you’ll have plenty to explore in leveraging the power of your GeForce RTX 50 Series GPU. For even more inspiration, check out NVIDIA’s content hub on how NVIDIA powers the AI world, along with this list of more than 100 RTX-accelerated creative apps that run local AI. NVIDIA hardware can power your AI projects today, and is ready to handle whatever comes throughout 2025 and beyond.
