How NVIDIA’s AI factory platform balances maximum performance and minimum latency, optimizing AI inference to power the next industrial revolution.
When we prompt generative AI to answer a question or create an image, large language models generate tokens of intelligence that combine to provide the result.
One prompt. One set of tokens for the answer. This is called AI inference.
One prompt. Many sets of tokens to complete the job.
AI factories generate AI tokens. Their product is intelligence. In the AI era, this intelligence grows revenue and profits. Growing revenue over time depends on how efficient the AI factory can be as it scales.
AI factories are the machines of the next industrial revolution.

Aerial view of Crusoe (Stargate)

CoreWeave, 200MW, USA, scaling globally
But ultimately, AI factories are limited by the power they can access.

But the real work happens in the space in between. Each dot along the curve represents batches of workloads for the AI factory to process — each with its own mix of performance demands.
NVIDIA GPUs have the flexibility to handle this full spectrum of workloads because they can be programmed using NVIDIA CUDA software.

Blackwell gets another boost when developers optimize the AI factory workloads autonomously with NVIDIA Dynamo, the new operating system for AI factories.
The improvements are remarkable. In a single generational leap of processor architecture from Hopper to Blackwell, we can achieve a 50x improvement in AI reasoning performance using the same amount of energy.
This is how NVIDIA full-stack integration and advanced software give customers massive speed and efficiency boosts in the time between chip architecture generations.

And with each push forward in performance, AI can create trillions of dollars of productivity for NVIDIA’s partners and customers around the globe — while bringing us one step closer to curing diseases, reversing climate change and uncovering some of the greatest secrets of the universe.
This is compute turning into capital — and progress.