Overview
How to Profitably Scale AI Inference?
AI inference—how we experience AI through chatbots, copilots, and creative tools—is scaling at a double exponential pace. User adoption is accelerating while the AI tokens generated per interaction, driven by agentic workflows, long-thinking reasoning, and mixture-of-experts (MoE) models, soars in parallel.
To enable inference at this massive scale, NVIDIA delivers data-center-scale architecture on an annual rhythm. Our extreme hardware and software codesign delivers order-of-magnitude leaps in performance and drives down the cost per token, making advanced AI experiences economically viable at scale.
NVIDIA GB300 NVL72 delivers 50x tokens per watt and 35x lower token cost over Hopper™, maximizing revenue within the same power budget and driving higher profit margins. Continuous software optimizations extract maximum performance at chip, rack, and data center scale, further improving return on investment over time.
Benefits
Highest Performance Maximizes Revenue
With extreme hardware and software codesign, NVIDIA GB300 NVL72 delivers 50x tokens per watt over Hopper, maximizing AI factory revenue within the same power budget. Continuous software optimizations extract maximum performance at chip, rack, and data center scale, further improving return on investment over time.
Lowest Token Cost Expands Profit Margins
NVIDIA GB300 NVL72 system delivers 35x lower cost per token over NVIDIA Hopper platform, driving higher profit margins for AI factories. With each generation, performance improvements far outpace infrastructure costs, creating better economics to enable advanced AI experiences at massive scale.
Full Stack Optimizes Every Model and Use Case
NVIDIA supports every model across generative AI, traditional ML, scientific computing, biology, and physical AI. From latency-sensitive real-time applications to high-throughput batch processing, NVIDIA delivers the best performance for every use case. The platform provides maximum flexibility and programmability to choose the optimal configuration for evolving workload and business requirements.
Native Integration Accelerates Deployment
NVIDIA’s production-ready software, including Dynamo and TensorRT™ LLM, and native integration with leading frameworks such as PyTorch, vLLM, SGLang, and llm-d, deliver the most robust AI inference stack. As model architectures and inference techniques rapidly evolve, NVIDIA’s stack ensures the fastest path from innovation to production.
Platform
Extreme Hardware–Software Codesign
Powerful hardware without smart orchestration wastes potential; great software without fast hardware means sluggish inference performance. NVIDIA’s inference platform delivers a continuously optimized full-stack solution with codesigned compute, networking, storage, and software to enable the highest performance across diverse workloads.
Explore some of the key NVIDIA hardware and software innovations.
Customer Stories
How Industry Leaders Are Driving Innovation With AI Inference
Resources
The Latest in AI Inference Resources
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Blogs
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Sessions
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Training
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Videos
Next Steps
