Coding assistants, powered by AI, are revolutionizing software development for both experienced and novice developers. Experienced developers benefit from staying focused on complex tasks, while newer coders accelerate learning with explanations and different implementation approaches. NVIDIA GeForce RTX GPUs provide the hardware acceleration needed for local coding assistants to operate effectively.

AI-powered coding assistants streamline mundane tasks in software development, freeing up time for problem-solving and design. These assistants are integrated into popular IDEs like Visual Studio Code and Pycharm, offering cloud-based or local options. Local coding assistants running on RTX GPUs offer cost-free access and increased efficiency for developers.

Tools like Continue.dev, Tabby, OpenInterpreter, and LM Studio make it easy to run coding assistants locally on RTX GPUs. These tools support models like Gemma 12B and Meta Llama 3.1-8B, providing personalized support and faster throughput compared to running on a CPU. RTX AI PCs enable developers to build, learn, and iterate faster with AI-powered tools.

For students and AI enthusiasts, NVIDIA GeForce RTX 50 Series laptops accelerate generative AI applications, making them ideal for learning, creating, and gaming. NVIDIA is hosting a Plug and Play: Project G-Assist Plug-In Hackathon to encourage developers to experiment with local AI and extend the capabilities of their RTX PCs. Join NVIDIA’s Discord server for discussions on RTX AI innovations and connect with community developers.

Read more at NVIDIA: Run Coding Assistants for Free on RTX AI PCs