How to Run Powerful LLMs Locally on Your RTX PC: A Guide to NVIDIA's AI Garage

Harness the power of large language models (LLMs) on your own computer without relying on cloud services thanks to advances in AI and NVIDIA’s RTX hardware. With NVIDIA RTX you are unlocking greater privacy, speed, and customization all without subscription fees or data caps.

Why Choose Local LLMs?

Running LLMs on your PC provides enhanced privacy and faster response times. You gain complete control over your data and can tailor your AI assistant to your unique needs. The emergence of open-weight models such as OpenAI’s gpt-oss and Alibaba’s Qwen 3 has made sophisticated AI accessible on consumer-grade hardware.

To make local AI accessible, NVIDIA has partnered with developers to supercharge leading LLM applications for RTX GPUs. Three standout tools make local AI simple and efficient:

Key Tools Optimized for RTX PCs

• Ollama: An open-source interface for LLM interaction. Ollama enables document analysis, multimodal workflows, and app integration. Major updates deliver:
  • Enhanced performance for gpt-oss-20B and Gemma 3 models
  • Support for efficient models, improving retrieval-augmented generation
  • Better memory handling and multi-GPU stability
    
    
• AnythingLLM: Built atop Ollama, this open-source app lets you create custom AI assistants. Features include document uploads, custom knowledge bases, and conversational interfaces—perfect for personalized, context-rich support.
  
  
• LM Studio: Based on llama.cpp, LM Studio offers a user-friendly way to run, chat with, and serve LLMs as local APIs. Recent improvements bring:
  • Support for NVIDIA’s Nemotron Nano v2 9B model
  • Flash Attention for up to 20% faster inference
  • CUDA kernel enhancements for speed
  • Simplified versioning for easy updates

Transforming Learning: The AI Study Buddy

Local LLMs are revolutionizing education. With AnythingLLM, students can upload syllabi, assignments, and textbooks to build a personalized AI tutor. You can:

• Generate flashcards from lecture slides
• Get answers to questions using your class notes
• Create and grade quizzes for exam prep
• Receive step-by-step solutions to homework

Professionals and hobbyists benefit as well, using these tools for certification preparation or project research, all with the performance boost of RTX GPUs.

Introducing Project G-Assist: Smarter PC Management

Project G-Assist is NVIDIA’s experimental AI assistant that streamlines gaming PC control through voice or text. Its latest features include:

• Automatic app profile switching for laptops (efficiency, quality, balance modes)
• BatteryBoost and WhisperMode for longer battery life and quieter operation
• Extensible plugin system for custom commands and integrations

With the G-Assist Plug-In Builder and Hub, you can expand the assistant’s functions, making PC management simpler and more intuitive.

Recent Highlights in the RTX AI Ecosystem

• Ollama and llama.cpp/GGML have received major performance upgrades, especially for new architectures.
  
  
• Project G-Assist now includes features tailored for laptops and improved natural language understanding.
  
  
• Windows ML with NVIDIA TensorRT is generally available, reducing inference times by up to 50% for LLMs and other models on Windows 11 PCs.
  
  
• The NVIDIA Nemotron model suite accelerates AI innovation across various industries.

NVIDIA’s RTX AI Garage ecosystem puts advanced LLMs at your fingertips, combining privacy, speed, and flexibility. Whether for education, productivity, or gaming, the latest tools and updates let you build AI-powered workflows—right on your RTX PC.

Source: NVIDIA Blog