AMD has launched the Client Tokenomics Calculator as a decision tool for CIOs and finance leaders wrestling with runaway cloud AI costs, arguing that a hybrid mix of local and cloud inference can cut three-year AI spend by 40 to 60 percent for mid-sized knowledge-worker fleets.
The web-based tool enables users to model three deployment scenarios — Cloud Only, Local (AMD) and Hybrid — across different fleet sizes and workload tiers, then outputs total cost of ownership (TCO) over one to five years, average monthly run rates, break-even timing and an auto-sized AMD hardware recommendation.
It is designed so help IT teams find the optimal split for before committing to any hardware investment.
For a medium workload tier representing a knowledge worker actively using an agent harness such as Claude Code, Codex or Hermes with roughly 5.7 million input tokens and 574,000 output tokens per user daily, AMD claims a 500-user hybrid deployment (50 percent local, 50 percent cloud) can deliver projected three-year savings of 40 to 60 percent versus cloud-only. Full local deployment pushes savings higher, with break-even typically achieved in under 24 months.
Much of today’s token burn comes from iterative prompt drafting and refinement that does not require frontier-model performance. When all of that iterative work runs through a cloud API, customers pay frontier model pricing for what is functionally a rough-draft scratchpad. By offloading that initial discussion to local inference on AMD Ryzen AI and Radeon hardware, enterprises can remove the per-token tax on initial conversation and prompt tightening.
Entelechy Asia 