The Institutional Standard for
AI Compute Valuation
A1 Benchmarks transforms fragmented, opaque cloud GPU pricing into verified, institutional-grade commodity benchmarks. Explore our surveillance breadth, econometric data treatment, and market-standard reference deliverables.
What We Scope: Complete Market Breadth
Cloud GPUs are sold across fragmented, opaque platforms with hidden chassis packaging and inconsistent availability. A1 Benchmarks continuously monitors and ingests the entire institutional compute footprint worldwide.
15+ Cloud Providers
Real-time surveillance across Hyperscalers (AWS, Azure, GCP, OCI), AI NeoClouds, and decentralized compute venues.
57 Hardware Architectures
Full-spectrum tracking across training clusters, inference nodes, and custom ASICs in SXM, PCIe, NVL, and OAM form factors.
Full-Stack Instance Topography
Disentangles pure accelerator silicon from host chassis vCPU, RAM, networking fabrics, and vendor packaging.
Multi-Tenor Pricing Vectors
Tracks instantaneous spot clearing alongside 1-month, 1-year, and 3-year enterprise committed rates.
How We Treat Data: Institutional Econometrics
Raw market feeds are riddled with broker noise, phantom capacity, and bundle markups. Our quantitative pipeline applies strict econometric treatments to isolate true commodity fair value.
Telemetry Verification & Anti-Spoofing
Filters synthetic bids, phantom capacity, and broker noise via the Honest Set protocol, flagging operational stockouts in real time.
Zero-Bias Commodity Decomposition
Decomposes instance prices into pure hardware components, directly attributing 100% of market value to physical silicon, memory, and fabric margin without bundled markup.
Dual Liquidity Weighting (CWAP & VWAP)
Balances immediately executable standby capacity (CWAP) against active workload consumption (VWAP) via inventory conservation.
Empirical Risk & Interruption Modeling
Models continuous hazard rates and recovery downtime to compute true risk-adjusted effective availability for training workloads.
Live Commodity Decomposition Explorer
Select an accelerator to see how our pipeline strips away bundled host markups to isolate pure silicon value in live market data:
What Comes Out: The Reference Layer for Compute Capital
Our methodology outputs actionable market intelligence, capital-efficient cloud procurement data, and auditable reference rates for institutional compute contracts.
Unbundled Pure-Silicon Spot Pricing
Standardized hourly rates for isolated GPU silicon, stripped of host packaging and provider distortions.
The A1 Benchmark Index Suite
Institutional reference indices tracking macro compute value, hardware premiums, and fleet deflation.
Workload Survival Curves
Empirical job survival probabilities across 1-hour, 6-hour, and 24-hour workload horizons.
Financial Settlement Reference Rates
Manipulation-resistant benchmark rates engineered for bilateral compute forwards, capacity hedging, and GPU debt underwriting.
Index Governance & Construction Protocols
All A1 Benchmarks indices adhere to strict, rule-based governance protocols designed to eliminate manipulation, look-ahead bias, and illiquidity artifacts.
Provider Diversity Gate
Hardware must be actively listed across at least 3 independent institutional providers to qualify for index inclusion, eliminating single-venue bias.
$1M+ Daily Implied Volume
Component SKUs must sustain $1,000,000+ in daily transactional volume, filtering out illiquid testbeds and hobbyist nodes.
Disciplined Quarterly Rebalancing
Indices rebalance on an audited quarterly schedule. New silicon enters as liquidity scales, while legacy hardware phases out without price discontinuities.
Zero Look-Ahead Bias
All pricing models, weights, and risk metrics operate strictly on trailing point-in-time windows, preserving causal chronology for backtesting.
Methodology Specifications Hub
For institutional risk desks, quantitative researchers, lending underwriters, and datacenter procurement leads requiring the formal mathematical proofs, parameter derivations, and technical rulebooks.
Global GPU Pricing & Econometric Specification
Complete mathematical architecture of the Generation 4 Unified Log-Log Hedonic Pricing Model. Deconstructs cloud GPU instances into pure per-chip silicon attributes (PFLOPs, memory bandwidth, vRAM), host infrastructure overhead, cluster packaging elasticities, and provider tier markups under dual CWAP and VWAP clearing regimes.
Implied Capacity & CWAP Methodology
Mathematical derivation of Capacity-Weighted Average Price (CWAP). Explains structural fleet anchoring across physical datacenter footprints, zonal presence partitioning, and supply convexity curves.
Implied Volume & VWAP Theoretical Architecture
The Inverse CWAP model for deriving active consumption and liquid trade flow. Formulates physical inventory conservation equations, 24-hour GPU-Hour scaling, and endogeneity-prevention bounds.
Spot Preemption Hazard Rate Specification
Empirical reliability modeling for cloud accelerators. Derives continuous preemption hazard rates, workload survival curves across 1h, 6h, and 24h horizons, and the Honest Set anti-spoofing filter.
The Risk-Adjusted Compute Yield Framework
Continuous stochastic recovery modeling under alternating renewal theory. Formulates effective availability discounting factors to evaluate net risk-adjusted earnings for GPU asset finance and yield indices.
Universal Benchmark Index Rulebook & Charter
Official governance rulebook governing all A1 Benchmark suites: Macro, Infrastructure, Yield, Hardware Lifecycle, Developer, and Volatility indices. Mandates multi-provider eligibility and audited backtesting standards.