The Economics of Agentic AI: Cost Advantages of Dell AI Factory with NVIDIA vs Public Cloud from Pilot to Scale
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Mitch Lewis
Compared with frontier APIs, savings can reach up to 93% for server solutions and 98% for desktop solutions.
As agentic AI reshapes enterprise deployment, economic impact has become the leading metric organizations use to justify AI investment, according to Futurum Research. Evaluating infrastructure choices for AI deployments requires understanding how price and performance interact to support a given workload. Today’s AI workloads are rapidly shifting from standard interactive chat applications to autonomous agentic workflows. This represents not only significant changes in the interaction and efficiency of AI, but also the economics of the supporting infrastructure.
This report evaluates the economics of running agentic AI workloads on premises with the Dell AI Factory with NVIDIA compared to open-weight and leading frontier cloud hosted models. The study utilizes performance results from eight distinct Dell platforms, modeling three separate agentic workloads over a 2 year time horizon.
Key findings include:
- The Dell AI Factory with NVIDIA portfolio delivers cost-optimized solutions across every workload profile evaluated.
- Dell hardware achieved a cost advantage in all configurations tested against AWS Bedrock and leading frontier APIs, with savings ranging from 8% to 98%.
- Advantages hold from single-workstation pilots through multi-server production deployments, across low, medium, and high task complexity, and across model sizes from 30 billion to 120 billion parameters.
- The largest configuration tested supported over 16,000 concurrent agents, while the architecture enables further scaling with additional nodes.
- Compared to open-weight model pricing on AWS Bedrock, Dell PowerEdge servers achieve up to 67.7% savings and Dell desktop systems achieve up to 89.8% savings.
- Compared to leading frontier API costs, Dell PowerEdge servers achieve up to 93.7% savings and Dell desktop systems achieve up to 98.4% savings.
Research commissioned by:
