NVIDIA Powering the Next Wave of AI Models
OpenAI has launched GPT 5.2, described as its most capable model series so far for professional knowledge work. Behind the scenes, this new AI model is trained and deployed on powerful NVIDIA infrastructure, including NVIDIA Hopper and the newer GB200 NVL72 systems.
While GPT 5.2 is an AI model focused on reasoning and knowledge tasks, the interesting part for tech and PC enthusiasts is the hardware story. Training these frontier models depends on huge GPU clusters, advanced networking and carefully tuned software stacks. NVIDIA has essentially built a full platform for AI compute at scale, similar to how high end gaming rigs combine powerful GPUs, fast memory and optimized drivers for maximum performance.
The company highlights how modern AI is driven by three scaling laws: pretraining, post training and test time scaling. Reasoning models are becoming more common and they often use multiple networks working together during inference. However, the core intelligence of these models still comes from massive pretraining and careful post training, which demand extreme compute resources.
GB200, GB300 and the Need for Massive GPU Scale
Training a frontier level AI model from scratch is not a small task. It can require tens of thousands or even hundreds of thousands of GPUs working in parallel. This is very different from a single gaming PC running a title at high frame rates, but the underlying idea is similar: more powerful GPUs and better architectures enable more performance.
NVIDIA emphasizes that this kind of scale needs excellence across several areas:
- World class accelerators, which are essentially very high end GPUs designed specifically for AI workloads.
- Advanced networking that can connect GPUs across scale up, scale out and scale across architectures.
- A fully optimized software stack so all this hardware is actually used efficiently.
Compared with the NVIDIA Hopper architecture, the NVIDIA GB200 NVL72 systems delivered three times faster training performance on the largest model tested in the latest MLPerf Training benchmarks. They also achieved nearly twice the performance per dollar. For developers and cloud providers this means shorter development cycles and quicker deployment of new AI models.
Going a step further, NVIDIA GB300 NVL72 delivers more than a four times speedup over Hopper. For anyone who follows GPU generations in gaming, this is like jumping several steps ahead in one go. These gains are not about a few extra frames per second but about enabling AI models that would have been impossible or far too slow on older hardware.
AI Across Modalities and What It Means for Tech
The majority of today’s leading large language models run on NVIDIA platforms, but AI is no longer just about text. NVIDIA supports development across multiple modalities, including speech, images, video and even areas like biology and robotics.
Some of the highlighted models include:
- Evo 2, which decodes genetic sequences.
- OpenFold3, which predicts 3D protein structures.
- Boltz 2, which simulates drug interactions to help find promising candidates faster.
In clinical environments, NVIDIA Clara synthesis models generate realistic medical images to improve screening and diagnosis while protecting patient data. This shows how the same class of GPUs that gamers recognize from the GeForce brand has evolved into specialized data center accelerators that power serious scientific and medical workloads.
On the creative and entertainment side, companies like Runway and Inworld also train on NVIDIA infrastructure. Runway recently announced Gen 4.5, a top rated video generation model according to the Artificial Analysis leaderboard. This model is optimized for NVIDIA Blackwell and was developed entirely on NVIDIA GPUs across research, pretraining, post training and inference.
Runway also introduced GWM 1, a general world model trained on NVIDIA Blackwell. It is designed to simulate reality in real time and is interactive, controllable and general purpose. This has clear implications for future video games, virtual worlds, education tools, science visualizations and robotics. Imagine AI driven environments that react intelligently in real time, powered by the same NVIDIA Blackwell architecture running in the cloud.
Blackwell in the Cloud and Data Centers
NVIDIA Blackwell is now widely available through major cloud service providers and server makers. There is also NVIDIA Blackwell Ultra, which offers even more compute power, memory and architectural improvements.
Cloud providers and NVIDIA Cloud Partners offering Blackwell powered instances include:
- Amazon Web Services
- Google Cloud
- Microsoft Azure
- Oracle Cloud Infrastructure
- CoreWeave
- Lambda
- Nebius
- Together AI
These platforms allow AI labs and developers to scale pretraining and other heavy workloads without owning the physical hardware. For PC and gaming enthusiasts this is similar in spirit to cloud gaming services but targeted at AI training instead of running games. The heavy lifting happens in data centers packed with NVIDIA accelerators, and users access that power remotely.
NVIDIA also points to its strong showing in the MLPerf Training 5.1 benchmarks, where it submitted results in all seven categories. This underlines how its hardware and software stack can handle a wide range of AI workloads efficiently. Data centers benefit by being able to run many types of jobs on a single unified platform, rather than maintaining separate systems for each task.
A growing list of leading AI labs, including Black Forest Labs, Cohere, Mistral, OpenAI, Reflection and Thinking Machines Lab, are training their models on the NVIDIA Blackwell platform. From frontier models like GPT 5.2 to more specialized systems in medicine, biology, video and robotics, much of the AI future is being built on these high performance GPU architectures.
For anyone interested in PC hardware, GPUs or cloud compute, this trend shows how NVIDIA’s expertise in graphics has evolved into a central role in global AI infrastructure. The same company that drives high frame rate gaming is now also powering the training of some of the most advanced AI systems in the world.
Original article and image: https://blogs.nvidia.com/blog/leading-models-nvidia/
