NVIDIA Blackwell Sets New Standard in InferenceMAX Benchmarks

As AI evolves from simple answers to complex reasoning, the demand for inference and its economic significance is rapidly increasing.

The newly introduced independent InferenceMAX v1 benchmarks are the first to measure the total cost of compute across real-world scenarios. The NVIDIA Blackwell platform excelled in these benchmarks, showcasing unmatched performance and efficiency.

A $5 million investment in an NVIDIA GB200 NVL72 system can generate $75 million in token revenue, indicating a 15x return on investment and highlighting the new economics of inference.

InferenceMAX v1 runs popular models across leading platforms, measuring performance for a wide range of use cases and publishing verifiable results. This benchmark underscores the importance of efficiency and economics in modern AI.

NVIDIA collaborates with OpenAI, Meta, and DeepSeek AI to optimize the latest models for the world's largest AI inference infrastructure, reflecting a broader commitment to open ecosystems and shared innovation.

Through hardware and software co-design optimizations, NVIDIA continuously improves performance. The release of TensorRT LLM v1.0 significantly enhances the speed and responsiveness of large AI models.

InferenceMAX uses the Pareto frontier to map performance, showing how NVIDIA Blackwell balances production priorities like cost, energy efficiency, throughput, and responsiveness.

NVIDIA's Think SMART framework aids enterprises in navigating the shift to AI factories, highlighting how NVIDIA's full-stack inference platform delivers real-world ROI by turning performance into profits.