The New Economy of AI Inference: A Key Driver

AI models have evolved from merely answering questions to reasoning through them, leading to increased computational costs. Inference, the process of running these models, is now a major factor driving AI compute expenses.

The InferenceMAX v1 benchmark is the first to measure total compute costs across real-world scenarios, with NVIDIA's Blackwell platform leading in performance and efficiency for large-scale AI operations.

Analysis shows that a $5 million NVIDIA GB200 NVL72 system can generate approximately $75 million in token revenue, representing a 15x return on investment, reshaping how companies approach AI inference infrastructure.

InferenceMAX v1 tests popular AI models on multiple platforms, evaluating performance across various workloads. The results provide transparency and reproducibility, offering insights into the real-world economics of AI computing.

NVIDIA's Blackwell platform is designed with tightly integrated hardware and software, using NVFP4 precision to enhance efficiency without sacrificing accuracy. This approach ensures scalable performance in real-world settings.

The AI industry is transitioning from pilots to AI factories, building infrastructure to convert data into tokens, predictions, and business decisions in real time. Open benchmarks like InferenceMAX help teams select the right hardware, manage costs, and plan for service-level targets.