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Nvidia today announced foundation models running locally on Nvidia RTX AI PCs that supercharge digital humans, content creation, productivity and development.
GeForce has long been a vital platform for AI developers. The first GPU-accelerated deep learning network, AlexNet, was trained on the GeForce GTXTM 580 in 2012 — and last year, over 30% of published AI research papers cited the use of GeForce RTX. Jensen Huang, CEO of Nvidia, made the announcement during his CES 2025 opening keynote.
Now, with generative AI and RTX AI PCs, anyone can be a developer. A new wave of low-code and no-code tools, such as AnythingLLM, ComfyUI, Langflow and LM Studio enable enthusiasts to use AI models in complex workflows via simple graphical user interfaces.
NIM microservices connected to these GUIs will make it effortless to access and deploy the latest generative AI models. Nvidia AI Blueprints, built on NIM microservices, provide easy-to-use, preconfigured reference workflows for digital humans, content creation and more.
To meet the growing demand from AI developers and enthusiasts, every top PC manufacturer and system builder is launching NIM-ready RTX AI PCs.
“AI is advancing at light speed, from perception AI to generative AI and now agentic AI,” said Huang. “NIM microservices and AI Blueprints give PC developers and enthusiasts the building blocks to explore the magic of AI.”
The NIM microservices will also be available with Nvidia Digits, a personal AI supercomputer that provides AI researchers, data scientists and students worldwide with access to the power of Nvidia Grace Blackwell. Project Digits features the new Nvidia GB10 Grace Blackwell Superchip, offering a petaflop of AI computing performance for prototyping, fine-tuning and running large AI models.
Making AI NIMble
Foundation models — neural networks trained on immense amounts of raw data — are the building blocks for generative AI.
Nvidia will release a pipeline of NIM microservices for RTX AI PCs from top model developers such as Black Forest Labs, Meta, Mistral and Stability AI. Use cases span large language models (LLMs), vision language models, image generation, speech, embedding models for retrieval-augmented generation (RAG), PDF extraction and computer vision.
“Making FLUX an Nvidia NIM microservice increases the rate at which AI can be deployed and experienced by more users, while delivering incredible performance,” said Robin Rombach, CEO of Black Forest Labs, oin a statement.
Nvidia today also announced the Llama Nemotron family of open models that provide high accuracy on a wide range of agentic tasks. The Llama Nemotron Nano model will be offered as a NIM microservice for RTX AI PCs and workstations, and excels at agentic AI tasks like instruction following, function calling, chat, coding and math. NIM microservices include the key components for running AI on PCs and are optimized for deployment across NVIDIA GPUs — whether in RTX PCs and workstations or in the
cloud.
Developers and enthusiasts will be able to quickly download, set up and run these NIM microservices on Windows 11 PCs with Windows Subsystem for Linux (WSL).
“AI is driving Windows 11 PC innovation at a rapid rate, and Windows Subsystem for Linux (WSL) offers a great cross-platform environment for AI development on Windows 11 alongside Windows Copilot Runtime,” said Pavan Davuluri, corporate vice president of Windows at Microsoft, in a statement. “Nvidia NIM microservices, optimized for Windows PCs, give developers and enthusiasts ready-to-integrate AI models for their Windows apps, further accelerating deployment of AI capabilities to Windows users.”
The NIM microservices, running on RTX AI PCs, will be compatible with top AI development and agent frameworks, including AI Toolkit for VSCode, AnythingLLM, ComfyUI, CrewAI, Flowise AI, LangChain, Langflow and LM Studio. Developers can connect applications and workflows built on these frameworks to AI models running NIM microservices through industry-standard endpoints, enabling them to use the latest technology with a unified interface across the cloud, data centers, workstations and PCs.
Enthusiasts will also be able to experience a range of NIM microservices using an upcoming release of the Nvidia ChatRTX tech demo.
Putting a Face on Agentic AI
To demonstrate how enthusiasts and developers can use NIM to build AI agents and assistants, Nvidia today previewed Project R2X, a vision-enabled PC avatar that can put information at a user’s fingertips, assist with desktop apps and video conference calls, read and summarize documents, and more.
The avatar is rendered using Nvidia RTX Neural Faces, a new generative AI algorithm that augments traditional rasterization with entirely generated pixels. The face is then animated by a new diffusion-based NVIDIA Audio2FaceTM-3D model that improves lip and tongue movement. R2X can be connected to cloud AI services such as OpenAI’s GPT4o and xAI’s Grok, and NIM microservices and AI Blueprints, such as PDF retrievers or alternative LLMs, via developer frameworks such as CrewAI, Flowise AI and Langflow.
AI Blueprints Coming to PC
NIM microservices are also available to PC users through AI Blueprints — reference AI workflows that can run locally on RTX PCs. With these blueprints, developers can create podcasts from PDF documents, generate stunning images guided by 3D scenes and more.
The blueprint for PDF to podcast extracts text, images and tables from a PDF to create a podcast script that can be edited by users. It can also generate a full audio recording from the script using voices available in the blueprint or based on a user’s voice sample. In addition, users can have a real-time conversation with the AI podcast host to learn more.
The blueprint uses NIM microservices like Mistral-Nemo-12B-Instruct for language, Nvidia Riva for text-to-speech and automatic speech recognition, and the NeMo Retriever collection of microservices for PDF extraction.
The AI Blueprint for 3D-guided generative AI gives 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 pre-packaged workflow powered by the FLUX NIM microservice will use the current composition to generate high-quality images that match the 3D scene.
Nvidia NIM microservices and AI Blueprints will be available starting in February. NIM-ready RTX AI PCs will be available from Acer, ASUS, Dell, GIGABYTE, HP, Lenovo, MSI, Razer and Samsung, and from local system builders Corsair, Falcon Northwest, LDLC, Maingear, Mifcon, Origin PC, PCS and Scan.
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