Reducing what gets sent addresses one side of an inference bill. The rest is what it takes to hold a model in memory and execute it. That side has been treated as a constant.
Ask what a model costs to run and the answer is a hardware requirement. The requirement is derived from three assumptions that are rarely questioned because they have always been true.
A model is loaded in full and stays loaded. Device memory is sized to the model rather than to the work being done.
Anything not resident has to cross a bus to get there. In practice the path to the device dominates the arithmetic performed once it lands.
A forward pass touches the whole network by default, whether or not the whole network contributes to the token being produced.
Each of the three constraints above has a corresponding line of work. Status is stated plainly: development means it runs, research means it does not yet.
Everything on the reduction side of the platform is measured against a provider's own invoice, which is why we are willing to state it. Runtime results are measured against our own hardware, and we have not finished the work.
Figures will appear here when they are reproducible by someone who is not us. Until then, the status column above is the whole claim.
Reduction and context are deployed, billing, and measured against your provider's invoice rather than ours.