AI inference economics

The control plane for AI inference economics.

Runtime control for inference economics. Vectris is building runtime control software designed to help inference teams identify and recover capacity trapped in existing GPU fleets.

No model retraining or new hardware required for the initial runtime path. Vectris observes inference state, memory movement, and execution behavior, then governs runtime decisions between frameworks and hardware.

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Inference waste calculator

Simulation / planning model

Estimate directional inference capacity before buying more hardware.

Adjust the assumptions to model the possible magnitude of recoverable capacity across an existing inference fleet. Results are planning estimates, not guaranteed savings.

Modeled annual opportunity $2.34M

Planning estimate only. Actual results require workload-specific testing. Token-cost savings are shown separately to help avoid double-counting.

Recovered GPUs100

Capacity effect1.10×Based on selected assumptions

Cost / 1M tokens$9.38

Fleet profile

Adjust the inputs below to model one planning scenario at a time.

Editable

Total inference GPUscurrent deployed fleetGPUs Value per GPU-hourrevenue or avoided cost$/hr Average utilizationtypical production load% Recoverable waste scenarioplanning assumption%

Scenario presets

Optional economics

Power per GPUfacility-inclusive estimatekW Electricity rateplanning input$/kWh GPU capex per unitall-in procurement estimate$/GPU Baseline cost / 1M tokenstoken-cost lens$/M Annual token volumemillions of tokensM tokens

Modeled recovered GPU-equivalent capacity 100 GPUs

Capacity-equivalent estimate: approximately 1,100 GPUs at this recovery scenario.

Recovered GPU-hours / year 744,600

Modeled GPU-hours available for additional throughput or capacity deferral.

Recovered capacity value $2.23M

Annual value using the selected GPU-hour economics.

Illustrative capex deferral $4.00M

Illustrative procurement deferral if recovered capacity substitutes for incremental demand.

Modeled energy opportunity $102.5K

1,139 MWh-equivalent annual opportunity if recovery reduces power proportionally.

Token-cost lens $104.2K

Token-cost lens: this scenario implies a cost-equivalent shift from $10.42 to $9.38 per 1M tokens before overhead validation.

This calculator is for planning purposes. Actual results depend on workload-specific baseline-versus-controlled testing, quality gates, overhead accounting, and hardware-counter review. For budgeting, use one primary economic lens at a time — capacity, capex, energy, or token cost — to avoid double-counting.

Technical briefing

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