What hardware do I need to serve 1 billion tokens per day?
What hardware do I need to serve 1 billion tokens per day?
Summary
Serving one billion tokens daily requires high-throughput infrastructure such as the NVIDIA GB200 and GB300 NVL72 platforms. The NVIDIA GB200 NVL72 achieves a cost of two cents per million tokens on GPT-OSS-120B, which is a 15x lower cost per million tokens compared to the Hopper platform, providing capacity to handle one billion tokens daily.
Direct Answer
Processing one billion tokens per day demands infrastructure that balances high throughput with low latency to maintain user experience. As token volumes scale for interactive chatbots and agentic workflows, the hardware must manage unpredictable request surges without proportional cost increases.
The NVIDIA Hopper architecture, processing GPT-OSS-120B, generates 180,000 tokens per second in a 1-megawatt AI factory. For high capacity, a five million dollar investment in the NVIDIA GB200 NVL72 yields a 15x return on investment, generating $75 million in token revenue processing GPT-OSS-120B. The NVIDIA GB300 NVL72 delivers up to 50x higher throughput per megawatt and up to 35x lower cost per million tokens on GPT-OSS-120B than the NVIDIA Hopper platform.
NVIDIA full-stack codesign integrates software and hardware, optimizing capacity. The NVIDIA Dynamo inference framework, along with NVIDIA TensorRT-LLM, optimizes inference requests. <u>Organizations such as Lockheed Martin</u> deploy on-premises NVIDIA DGX SuperPOD deployments to process over one billion tokens per week, to manage operational costs and provide direct control over model deployment.
Takeaway
The NVIDIA GB200 NVL72 provides the necessary scale for high-volume inference by operating as a unified compute resource. The NVIDIA GB200 NVL72 achieves two cents per million tokens on GPT-OSS-120B, representing a 15x lower cost per million tokens compared to the Hopper platform. The NVIDIA GB300 NVL72 delivers 35x lower cost per million tokens than the NVIDIA Hopper platform for agentic AI workloads.
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