Generative AI is unlocking new capabilities for PCs and workstations, including game assistants, enhanced content-creation and productivity tools and more.NVIDIA NIM microservices, available now, and AI Blueprints, coming in April, accelerate AI development and improve its accessibility. Announced at the CES trade show in January, NVIDIA NIM provides prepackaged, state-of-the-art AI models optimized for the NVIDIA RTX platform, including the NVIDIA GeForce RTX 50 Series and, now, the new NVIDIA Blackwell RTX PRO GPUs. The microservices are easy to download and run. They span the top modalities for PC development and are compatible with top ecosystem applications and tools.
The experimental System Assistant feature of Project G-Assist was also released today. Project G-Assist showcases how AI assistants can enhance apps and games. The System Assistant allows users to run real-time diagnostics, get recommendations on performance optimizations, or control system software and peripherals - all via simple voice or text commands. Developers and enthusiasts can extend its capabilities with a simple plug-in architecture and new plug-in builder.
Amid a pivotal moment in computing - where groundbreaking AI models and a global developer community are driving an explosion in AI-powered tools and workflows - NIM microservices, AI Blueprints and G-Assist are helping bring key innovations to PCs. This RTX AI Garage blog series will continue to deliver updates, insights and resources to help developers and enthusiasts build the next wave of AI on RTX AI PCs and workstations.
Ready, Set, NIM! Though the pace of innovation with AI is incredible, it can still be difficult for the PC developer community to get started with the technology.
Bringing AI models from research to the PC requires curation of model variants, adaptation to manage all of the input and output data, and quantization to optimize resource usage. In addition, models must be converted to work with optimized inference backend software and connected to new AI application programming interfaces (APIs). This takes substantial effort, which can slow AI adoption.
NVIDIA NIM microservices help solve this issue by providing prepackaged, optimized, easily downloadable AI models that connect to industry-standard APIs. They're optimized for performance on RTX AI PCs and workstations, and include the top AI models from the community, as well as models developed by NVIDIA.
NIM microservices support a range of AI applications, including large language models (LLMs), vision language models, image generation, speech processing, retrieval-augmented generation (RAG)-based search, PDF extraction and computer vision. Ten NIM microservices for RTX are available, supporting a range of applications, including language and image generation, computer vision, speech AI and more. Get started with these NIM microservices today:
Language and Reasoning: Deepseek-R1-distill-llama-8B, Mistral-nemo-12B-instruct, Llama3.1-8B-instruct
Image Generation: Flux.dev
Audio: Riva Parakeet-ctc-0.6B-asr, Maxine Studio Voice
RAG: Llama-3.2-NV-EmbedQA-1B-v2
Computer Vision and Understanding: NV-CLIP, PaddleOCR, Yolo-X-v1
NIM microservices are also available through top AI ecosystem tools and frameworks.
For AI enthusiasts, AnythingLLM and ChatRTX now support NIM, making it easy to chat with LLMs and AI agents through a simple, user-friendly interface. With these tools, users can create personalized AI assistants and integrate their own documents and data, helping automate tasks and enhance productivity.
For developers looking to build, test and integrate AI into their applications, FlowiseAI and Langflow now support NIM and offer low- and no-code solutions with visual interfaces to design AI workflows with minimal coding expertise. Support for ComfyUI is coming soon. With these tools, developers can easily create complex AI applications like chatbots, image generators and data analysis systems.
In addition, Microsoft VS Code AI Toolkit, CrewAI and Langchain now support NIM and provide advanced capabilities for integrating the microservices into application code, helping ensure seamless integration and optimization.
Visit the NVIDIA technical blog and build.nvidia.com to get started.
NVIDIA AI Blueprints Will Offer Pre-Built Workflows NVIDIA AI Blueprints, coming in April, give AI developers a head start in building generative AI workflows with NVIDIA NIM microservices.
Blueprints are ready-to-use, extensible reference samples that bundle everything needed - source code, sample data, documentation and a demo app - to create and customize advanced AI workflows that run locally. Developers can modify and extend AI Blueprints to tweak their behavior, use different models or implement completely new functionality.
PDF to podcast AI Blueprint coming soon. The PDF to podcast AI Blueprint will transform documents into audio content so users can learn on the go. By extracting text, images and tables from a PDF, the workflow uses AI to generate an informative podcast. For deeper dives into topics, users can then have an interactive discussion with the AI-powered podcast hosts.
The AI Blueprint for 3D-guided generative AI will give artists finer control over image generation. While AI can generate amazing images from simple text prompts, controlling image composition using only words can be challenging. With this blueprint, creators can use simple 3D objects laid out in a 3D renderer like Blender to guide AI image generation. The artist can create 3D assets by hand or generate them using AI, place them in the scene and set the 3D viewport camera. Then, a prepackaged workflow powered by the FLUX NIM microservice will use the current composition to generate high-quality images that match the 3D scene.
NVIDIA NIM on RTX With Windows Subsystem for Linux One of the key tech
