LAS VEGAS, Jan. 6, 2025 (GLOBE NEWSWIRE) — CES — NVIDIA today announced core models running natively on NVIDIA RTX™ AI PCs that power digital humans, content creation, productivity and development.
These models “offered as NVIDIA NIM™ microservices” are accelerated by the new GeForce RTX™ 50 Series GPUs, which have up to 3.352 trillion operations per second of AI performance and 32 GB of VRAM. Built on the NVIDIA Blackwell architecture, the RTX 50 series are the first consumer GPUs to add support for FP4 computing, increasing AI inference performance by 2x and enabling generative AI models to run locally with a smaller memory footprint, compared to the previous generation of hardware.
GeForce™ has long been a vital platform for AI developers. The first GPU-accelerated deep learning network, AlexNet, was trained on a GeForce GTX™ 580 in 2012, and last year more than 30% of published AI research papers reported using GeForce RTX.
Now, with generative AI and RTX AI computing, 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 through simple graphical user interfaces.
NIM microservices associated with these GUIs will facilitate access and implementation of 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 with GeForce RTX 50 series GPUs.
AI is advancing at the speed of light, from perceptual AI to generative AI and now agent AI, said Jensen Huang, founder and CEO of NVIDIA. NIM microservices and AI Blueprints give PC developers and enthusiasts the foundation to explore the magic of AI.
Making AI NIMble
Fundamental models of “neural networks trained on massive amounts of raw data” are the foundation of generative artificial intelligence.
NVIDIA will release a number of NIM microservices for RTX AI PCs from top model developers such as Black Forest Labs, Meta (NASDAQ:), Mistral and Stability AI. Use cases include large-scale language models (LLM), vision language models, image generation, speech, embedding models for generating augmented search (RAG), PDF extraction, and computer vision.
The GeForce RTX 50 series GPUs with FP4 computing will unlock a huge range of PC-capable models that were previously limited to large data centers, said Robin Rombach, CEO of Black Forest Labs. Turning FLUX into an NVIDIA NIM microservice increases the speed at which AI can be deployed and experienced by multiple users, while delivering incredible performance.
NVIDIA also announced today the Llama Nemotoron family of open source models that deliver high accuracy across a wide range of agent tasks. The Llama Nemotron Nano model will be offered as a NIM microservice for RTX AI PCs and workstations, and excels at agent AI tasks such as following instructions, calling functions, chat, coding and math.
NIM microservices include key components for running artificial intelligence on PCs and are optimized for deployment on NVIDIA GPUs “whether on RTX PCs and workstations or in the cloud.
Developers and enthusiasts will be able to quickly download, deploy, and run these NIM microservices on Windows 11 PCs running the Windows Subsystem for Linux (WSL).
AI is rapidly driving Windows 11 PC innovation, and the Windows Subsystem for Linux (WSL) offers a great cross-platform environment for developing artificial intelligence on Windows 11 with the Windows Copilot Runtime, said Pavan Davuluri, corporate vice president of Windows at Microsoft ( NASDAQ: ). Optimized for Windows PCs, NVIDIA NIM microservices provide developers and enthusiasts with ready-to-integrate AI models for their Windows applications, further accelerating the deployment of AI capabilities for Windows users.
NIM microservices, running on RTX AI PCs, will be compatible with leading 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 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 number of NIM microservices using the upcoming release of the NVIDIA ChatRTX technology demo.
Putting a face on Agentic AI
To demonstrate how enthusiasts and developers can use NIM to build AI agents and assistants, NVIDIA today unveiled Project R2X, a vision-enabled computer avatar that can put information at the user’s fingertips, help with desktop applications and video conferencing, read and compress documents, and more.
The avatar is rendered using NVIDIA RTX Neural Faces, a new generative AI algorithm that augments traditional rasterization with fully generated pixels. The face is then animated by the new NVIDIA Audio2Face™-3D diffusion-based model that enhances lip and tongue movement. R2X can connect to cloud AI services such as OpenAI GPT4o and xAI Grok, and NIM microservices and AI Blueprints, such as PDF retrievers or alternative LLMs, through development frameworks such as CrewAI, Flowise AI and Langflow. Sign up for Project R2X updates.
AI designs are coming to PC
NIM microservices are also available to PC users via AI Blueprints ” references of AI workflows that can be run locally on RTX computers. Using these blueprints, developers can create podcasts from PDF documents, generate stunning visuals driven by 3D scenes, and more.
Draft PDF to Podcast extracts text, images, and tables from PDF to create a podcast script that users can edit. It can also generate full audio from a script using the voices available in the draft or based on the user’s voice sample. Additionally, users can chat in real-time with an AI podcast host to learn more about specific topics.
The blueprint uses NIM microservices such as 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.
AI Blueprint for 3D-driven generative AI gives artists finer control over image creation. Although artificial intelligence can generate amazing images from simple text queries, managing the composition of an image using only words can be challenging. With this blueprint, creators can use simple 3D objects placed in a 3D renderer like Blender to direct AI image generation. An artist can create 3D elements by hand or generate them using artificial intelligence, place them in the scene and set up the camera for 3D rendering. 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 microservices and AI Blueprints will be available starting in February with initial hardware support for GeForce RTX 50 series, GeForce RTX 4090 and 4080, and NVIDIA RTX 6000 and 5000 professional GPUs. Additional GPUs will be supported in the future.
NIM-ready RTX AI PCs will be available from Acer (TW:), ASUS, Dell (NYSE:), GIGABYTE, HP (NYSE:), Lenovo, , Razer and Samsung (KS:), and from local system manufacturers Corsair, Falcon Northwest, LDLC, Maingear, Mifcon, Origin PC , PCS and scanning.
Learn more about how NIM microservices, AI Blueprints, and NIM-ready RTX AI computing are accelerating generative AI by joining NVIDIA at CES.
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Certain statements in this press release including, but not limited to, statements about: the benefits, impact, performance and availability of our products, services and technologies, including NVIDIA RTX AI computing, GeForce RTX 50 Series GPUs, NVIDIA Blackwell architecture, GeForce GTX 580, Project R2X, NVIDIA ACE and NIM microservices, NVIDIA AI Blueprints, NVIDIA Grace Blackwell platform, Llama Nemotoron, NVIDIA ChatRTX, NVIDIA RTX Neural Faces, NVIDIA Audio2Face-3D model, Mistral-Nemo-12B-Instruct for language, NVIDIA Riva, NeMo Retriever, FLUX NIM microservice, GeForce RTX 4090 and 4080 and NVIDIA RTX 6000 and 5000 professional third-party GPUs that use or adopt NVIDIA products and technologies, and the advantages and influence thereof; and artificial intelligence advancing at the speed of light, from perceptual artificial intelligence to generative artificial intelligence and now agentic artificial intelligence are forward-looking statements that are subject to risks and uncertainties that could cause results to be materially different than expected. Important factors that could cause actual results to differ materially include: global economic conditions; our reliance on third parties to manufacture, assemble, package and test our products; impact of technological development and competition; developing new products and technologies or improving our existing products and technologies; market acceptance of our products or those of our partners; design, manufacturing or software defects; changes in consumer preferences or requirements; changes in industry standards and interfaces; unexpected loss of performance of our products or technologies when integrated into systems; as well as other factors set forth from time to time in NVIDIA’s most recent reports filed with the Securities and Exchange Commission or the SEC, including, but not limited to, its Annual Report on Form 10-K and Quarterly Reports on Form 10-Q . Copies of the reports filed with the SEC are posted on the company’s website and are available from NVIDIA free of charge. These forward-looking statements are not guarantees of future performance and speak only as of this date, and, except as required by law, NVIDIA disclaims any obligation to update these forward-looking statements to reflect future events or circumstances.
Many of the products and features described here remain in various stages and will be offered as and when they become available. The above statements are not intended to be, and should not be construed as, a commitment, promise, or legal obligation, and the development, release, and timing of any features or functionality described for our products are subject to change and remain at the sole discretion of NVIDIA. NVIDIA shall have no liability for non-delivery or delay in delivery of any product, feature or function described herein.
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AI core models for RTX AI computers
NVIDIA NIM microservices make it easy to access and deploy the latest generative AI models. NVIDIA AI Blueprints, built on NIM microservices, provide preconfigured reference workflows for digital humans, content creation, and more.
Source: NVIDIA
