--- title: "Compute economics & evidence | Aguasto" description: "Connect a declared cost and operating boundary to successful, quality-qualified output instead of an unsupported efficiency headline." canonical: "https://www.aguasto.com/topics/compute-economics" last-updated: "2026-10-13" --- # Compute economics & evidence | Aguasto Canonical HTML: [Compute economics & evidence](https://www.aguasto.com/topics/compute-economics) > Connect a declared cost and operating boundary to successful, quality-qualified output instead of an unsupported efficiency headline. [Aguasto](https://www.aguasto.com/) [Research topics](https://www.aguasto.com/topics) Compute economics & evidence [Resources](https://www.aguasto.com/resources) [Topics](https://www.aguasto.com/topics) [GPU Library](https://www.aguasto.com/gpus) [Model Index](https://www.aguasto.com/models) [Inference Stack](https://www.aguasto.com/inference-stack) [Learn](https://www.aguasto.com/learn) [Insights](https://www.aguasto.com/insights) [Research](https://www.aguasto.com/research) [Engineering tools](https://www.aguasto.com/tools) [Glossary](https://www.aguasto.com/glossary) [Methods](https://www.aguasto.com/methodologies) Aguasto / Research path ## Compute economics & evidence Connect a declared cost and operating boundary to successful, quality-qualified output instead of an unsupported efficiency headline. Evidence before conclusions Read the mechanism, inspect its sources and carry the stated boundaries into your own evaluation. [How Aguasto Research works](https://www.aguasto.com/methodologies) Aguasto Research · Revision 1 Editorial record: 2026-10-13 [Review and correction policy ↗](https://www.aguasto.com/methodologies#review) ### What was counted, and what useful work was delivered? A hardware specification, an electricity ratio and a model-service price answer different questions. Facility overhead is not a measure of model quality. An announced development scope is not commissioned IT load. A unit-cost calculation needs a cost boundary, a time period and a denominator that treats failures, retries and output quality consistently. Keep input assumptions separate from measured observations and from commercial commitments. Report utilization, acceptance, costs and token counts at compatible boundaries. Public operators’ disclosures can inform a case analysis, but they do not independently establish Aguasto costs, operating results, customers or financing outcomes. ### Follow the evidence. - #### Expose the calculation The tools show their formulas and bounds. Weight memory is a theoretical payload estimate; electricity scenarios omit costs outside their stated scope. Cost per million completed tokens divides a declared cost by a declared output count, and must not be mistaken for Aguasto token pricing. [Engineering tools ↗](https://www.aguasto.com/tools) Inspect hypothetical inputs, formulas and exclusions.[Calculation policy ↗](https://www.aguasto.com/methodologies#calculations) Units, sensitivity and reproducibility. - #### Keep efficiency and service outcomes separate Power usage effectiveness compares facility energy with IT energy under a stated boundary. It does not establish how many useful model responses the IT equipment produced. Compare task quality, workload, location, reporting period and completed-request behavior before making an economic or environmental inference. [PUE, WUE and useful compute ↗](https://www.aguasto.com/learn/measuring-pue-wue-and-ai-compute-efficiency) Separate infrastructure ratios from task-level output.[Dedicated and shared inference ↗](https://www.aguasto.com/insights/dedicated-and-shared-inference-economics) Inspect operating assumptions rather than a price promise. - #### Read reported milestones as evidence Track the operator, date, unit and status attached to each disclosure. Announced, financed, contracted, ready-for-service and operating scope can overlap. Do not add rows without a common boundary or treat a corporate release as independent commissioning evidence. [Industry case analyses ↗](https://www.aguasto.com/research/cases) Dated third-party disclosures and explicit unknowns.[Evidence classes ↗](https://www.aguasto.com/methodologies#claims) Distinguish attributed claims, analysis and scenarios. ### Cornerstone resources insights / Source-backed #### Dedicated compute and shared inference: compare the whole workload Provide a defensible cost-comparison method that includes idle reservation, completed tokens, operating scope and latency rather than a universal break-even claim. Source dates and scope in the reference [Dedicated compute and shared inference: compare the whole workload](https://www.aguasto.com/insights/dedicated-and-shared-inference-economics) learn / Source-backed #### Measuring PUE, WUE and AI Compute Efficiency at the Right Boundary Build a measurement framework that connects facility overhead and water intensity to useful compute, without confusing device telemetry, ratios or hypothetical arithmetic with operating results. Source dates and scope in the reference [Measuring PUE, WUE and AI Compute Efficiency at the Right Boundary](https://www.aguasto.com/learn/measuring-pue-wue-and-ai-compute-efficiency) case / Source-backed #### Core Scientific: reading contracted, energized and billed capacity Analyze dated public infrastructure disclosures with strict measurement/status distinctions; this is an independent third-party case, not an Aguasto customer story. Source dates and scope in the reference [Core Scientific: reading contracted, energized and billed capacity](https://www.aguasto.com/research/cases/core-scientific-capacity-disclosures) ### Continue the research [Applied Digital: Reading the Polaris Forge 1 Delivery Milestones](https://www.aguasto.com/research/cases/applied-digital-polaris-forge-capacity-milestones) [Crusoe Abilene: Separate Delivered Infrastructure from Expansion Plans](https://www.aguasto.com/research/cases/crusoe-abilene-delivery-and-expansion) ### Keep these boundaries close. [Power usage effectiveness (PUE) ↗](https://www.aguasto.com/glossary#pue) [Quality-qualified output ↗](https://www.aguasto.com/glossary#qualified-output) [Ready for service (RFS) ↗](https://www.aguasto.com/glossary#rfs) [Utilization ↗](https://www.aguasto.com/glossary#utilization) ### From research to qualification A development discussion, without promised financial results. Aguasto’s commercial offerings remain in development. No available capacity, live model API, commercial reservation or procurement relationship is implied by this research. [Explore the operating and capital thesis ↗](https://www.aguasto.com/development) ### Sources & verification The register preserves each source's publication and verification date. Manufacturer claims and documentation are attributed; Aguasto has not run the cited products in production. - [Dedicated Model Inference — Together AI ↗](https://www.together.ai/dedicated-model-inference) Provider distinguishes per-token shared service and GPU-hour dedicated resource billing; Dedicated and serverless are provider-specific service categories. Publication: date not stated in the reviewed source. Verified: 2026-10-12. - [Dedicated vs Serverless models — Together AI Knowledge Base ↗](https://support.together.ai/articles/2226355974-dedicated-vs-serverless-models) Dedicated hardware has cost while idle; High utilization changes economic comparison. Publication: date not stated in the reviewed source. Verified: 2026-10-12. - [Autoscaling — Baseten official documentation ↗](https://docs.baseten.co/deployment/autoscaling/overview) Independent replicas; minimum/maximum capacity; Scale-to-zero and startup billing/cold-start latency; Running-replica billing boundary is provider-specific. Publication: date not stated in the reviewed source. Verified: 2026-10-12. - [Best Practices Guide for Energy-Efficient Data Center Design — DOE FEMP, July 2024 ↗](https://www.energy.gov/sites/default/files/2024-07/best-practice-guide-data-center-design_0.pdf) PUE measures supporting infrastructure rather than IT productivity; Annual PUE and site/source WUE distinctions; Heat-reuse host and backup heat rejection. Publication: 2024-07-26. Verified: 2026-10-13. - [Quantifying the impact on PUE and energy consumption when introducing liquid cooling — Vertiv/NVIDIA study summary ↗](https://www.vertiv.com/en-us/about/news-and-events/articles/blog-posts/quantifying-data-center-pue-when-introducing-liquid-cooling/) Cooling changes can affect both sides of the PUE ratio; Vendor-modeled configurations are not universal measured savings. Publication: 2023-02-15. Verified: 2026-10-13. - [Recommendations for Measuring and Reporting Overall Data Center Efficiency, version 2 — DOE-hosted industry task force ↗](https://www1.eere.energy.gov/manufacturing/datacenters/pdfs/task_force_metrics_recommendations.pdf) Dedicated and mixed-use measurement boundaries; Metering categories and disclosed assumptions; Comparisons need climate and reliability context. Publication: 2011-05-17. Verified: 2026-10-13. - [HPC Data Center Power Usage Effectiveness — National Laboratory of the Rockies ↗](https://www.nlr.gov/computational-science/measuring-efficiency-pue) Example of metered support loads and attributed shared loads; Site-specific ESIF reporting; not an Aguasto benchmark. Publication: date not stated in the reviewed source. Verified: 2026-10-13. - [Cooling Water Efficiency Opportunities for Federal Data Centers — DOE FEMP ↗](https://www.energy.gov/cmei/femp/cooling-water-efficiency-opportunities-federal-data-centers) Closed equipment loop can reject to an evaporative tower; Annual site WUE definition; Treatment can add electricity and maintenance. Publication: 2019-01-09. Verified: 2026-10-13. - [Device Queries: Total Energy Consumption and Power Usage — NVIDIA NVML API Reference ↗](https://docs.nvidia.com/deploy/nvml-api/latest/api/group__nvmlDeviceQueries.html) GPU energy counter in millijoules since driver reload; Power sampling behavior and unsupported-feature errors; Device telemetry does not meter all facility loads. Publication: date not stated in the reviewed source. Verified: 2026-10-13. - [Data Center Metering and Resource Guide — DOE Better Buildings ↗](https://betterbuildingssolutioncenter.energy.gov/resources/data-center-metering-and-resource-guide) Metering enables efficiency diagnosis and verification; Separate planning guidance from dated market statistics. Publication: 2016-07-28. Verified: 2026-10-13. - [United States Data Center Energy Usage Report: 2025 Update — LBNL, published June 2026 ↗](https://escholarship.org/content/qt33m6w3x0/qt33m6w3x0.pdf) 2030 reference case and sensitivity scenarios; Idle draw, utilization and lifetime assumptions; Consumption forecasts do not establish available grid capacity. Publication: 2026-06-18. Verified: 2026-10-13. - [Core Scientific Form 8-K Exhibit 99.2 — project disclosure ↗](https://investors.corescientific.com/sec-filings/all-sec-filings/content/0001193125-26-165121/d149019dex992.htm) Approximately 590 MW contracted net critical IT versus 900 MW secured grid capacity; Approximately 350 MW energized and over 185 MW billed as of March 13 2026; Phased delivery and completion expectations are forward-looking. Publication: 2026-04-21. Verified: 2026-10-12. - [Core Scientific Announces Second Quarter 2026 Results ↗](https://investors.corescientific.com/news-events/press-releases/detail/139/core-scientific-announces-second-quarter-2026-results) 395 billing MW at Q2 end and 437 as of mid-July; Approximately 1.1 GW total leased customer power capacity includes expanded portfolio; Potential contracted revenue distinct from quarter revenue. Publication: 2026-07-28. Verified: 2026-10-12. ### In this research path [The decision](https://www.aguasto.com/topics/compute-economics#decision) [Reading sequence](https://www.aguasto.com/topics/compute-economics#reading-path) [Cornerstone resources](https://www.aguasto.com/topics/compute-economics#cornerstones) [Useful definitions](https://www.aguasto.com/topics/compute-economics#definitions) [Sources and verification](https://www.aguasto.com/topics/compute-economics#sources) [All research paths ↗](https://www.aguasto.com/topics) ## Company navigation - [Home](https://www.aguasto.com/) - [Infrastructure](https://www.aguasto.com/infrastructure) - [GPU Cloud](https://www.aguasto.com/gpu-cloud) - [AI Inference](https://www.aguasto.com/ai-inference) - [Development & Investment](https://www.aguasto.com/development) - [Company](https://www.aguasto.com/company) - [Contact](https://www.aguasto.com/contact) - [Privacy](https://www.aguasto.com/privacy) - [Research topics](https://www.aguasto.com/topics) - [GPU systems & local clusters](https://www.aguasto.com/topics/gpu-systems) - 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