Issue 01 · Week 17 of 2026.

The four-category scorecard. Where capital is going in, where revenue is coming out, and how much of it is real. The one chart for the boardroom.

• Frontier Labs

  OpenAI, Anthropic, Google DeepMind, xAI

  Capital In

  ~$50B ↑

  vs ~$30B

  Revenue Out

  ~$30B ↑

  vs ~$25B

  Burn / Rev

  0.6

  Movement

  Anthropic +8.5 GW across NVIDIA, Trainium, TPU — forward-buy that locks in vendor diversity and outruns disclosed demand.

• Hyperscaler-Hosted

  AWS Bedrock, Azure Foundry, Vertex, OCI

  Capital In

  ~$48B ↑

  vs ~$30B

  Revenue Out

  ~$10B ↑

  vs ~$8B

  Burn / Rev

  0.21

  Movement

  Microsoft absorbs ~1.6 GW from Stargate Abilene — orphaned frontier capacity rerouted into hyperscaler platforms.

• Neoclouds

  CoreWeave, Crusoe, Nebius, Applied Digital

  Capital In

  ~$15B ↑

  vs ~$10B

  Revenue Out

  $1.6B ↑

  vs $1.1B

  Burn / Rev

  0.4

  Movement

  CoreWeave backlog +4x YoY to $66.8B (incl. Meta $21B six-year) — conversion velocity is now the metric, not gross backlog.

• On-Prem / Hybrid

  Enterprise GPU clusters, sovereign and national programs

  Capital In

  ~$42B ↑

  vs ~$25B

  Revenue Out

  Indirect →

  vs Indirect

  Burn / Rev

  n/a

  Movement

  DeepSeek V4 open crosses frontier; sovereign programs surge — workload migration from rented to owned compute has a frontier-class trigger.

Burn-to-Revenue is revenue divided by committed capital. Lower means more capital is going out than coming in.

Each claim is scored 1–5 on source quality and triangulation. Anything 2 or below is flagged as noise. Where consensus is wrong, we say so.

• 5 / 5

  Anthropic has committed to ~8.5+ GW of forward compute capacity across NVIDIA, AWS Trainium, and Google TPU.

  Sources: anthropic.com (Apr 20 + Apr 7), AWS news, Verge, Broadcom 8-K, multiple SEC filings

  Real. The largest single-counterparty compute commitment ever recorded. Distributed across three platforms reduces single-vendor dependency and is critical evidence for the all-three-lenses thesis.

• 4 / 5

  Aggregate 2026 hyperscaler capex tracking ~$700B (Microsoft + Google + Meta + Amazon + Oracle).

  Sources: Composite of Q4 2025 earnings guides; not a single sourced number

  Directionally correct. Will likely revise upward on Q1 2026 prints (Apr 29 - May 6). Caution: the aggregate hides per-company variance — Microsoft is decelerating Azure guidance while Google capex still accelerates.

• 2 / 5 — noise

  DeepSeek V4 was trained end-to-end on Huawei Ascend silicon, eliminating NVIDIA dependency.

  Sources: Chinese-language tech blogs only. No primary DeepSeek confirmation.

  Noise. Significant if true (sovereign-AI hardware decoupling milestone) but unverified. Watch for any DeepSeek primary source. If confirmed, this advances the on-prem-via-non-Western-stack thesis materially.

• 4 / 5

  Anthropic withheld 'Mythos' on cyber-risk; UK AISI confirmed autonomous offensive capability.

  Sources: anthropic.com, red.anthropic.com, aisi.gov.uk, Cloud Security Alliance

  Real. First major lab to deliberately withhold a flagship on capability-risk grounds. Procurement diligence implications: cyber-capability gating becomes a vendor-risk criterion.

• 5 / 5

  Open-weight models now lead closed models on credible coding benchmarks.

  Sources: HuggingFace model cards (Kimi K2.6, GLM-5.1), Artificial Analysis, multiple independent evals

  Real. SWE-Bench Pro: Kimi K2.6 58.6, GLM-5.1 58.4 vs GPT-5.4 57.7, Opus 4.6 57.3. First time open leads closed on a credible code benchmark. The on-prem demand catalyst for the open-weights hypothesis.

Current vs prior period. Each metric has a threshold where the read materially changes — this panel flags the inflection before it lands in headlines. Click any metric for the methodology and this-week read.

• Frontier lab cash position (avg months runway, top 3)

  ~22 mo↓vs ~26 mo

  Threshold: <18 mo triggers re-rating risk

  What this measures

  Top 3 frontier labs (OpenAI, Anthropic, Google DeepMind) by disclosed runway, computed from cash on hand divided by trailing-12-month operating burn. The drop from ~26 to ~22 months reflects accelerating compute commitments outpacing revenue growth. <18 months triggers re-rating risk — investor models start pricing dilution or strategic exit; <12 months forces consolidation, acquisition, or revenue reset.

• Hyperscaler capex / AI revenue ratio (top 4 weighted)

  ~5.5↑vs ~4.8

  Threshold: >6.0 invites investor pushback at next earnings

  What this measures

  Top 4 hyperscalers (MSFT, GOOG, META, AMZN) weighted aggregate of total capex divided by AI-attributable revenue. ~5.5 means $5.50 of capex deployed per $1 of AI-attributable revenue. >6.0 is the threshold where sell-side analysts stop accepting the platform-pull-through narrative; sustained 5.5x+ is the wedge against capital-efficiency claims.

• CoreWeave revenue backlog

  $66.8B↑vs $15.1B

  Threshold: Conversion velocity matters more than gross figure

  What this measures

  Booked but unrecognized revenue. The 4x YoY jump reflects the new Meta $21B/6yr commitment plus Microsoft and OpenAI extensions. The metric to actually watch is conversion velocity: how quickly capacity comes online and customers ramp. If Meta recapitalizes its in-house compute and pulls back, this number compresses materially.

• NVIDIA Q-over-Q data center revenue

  $62.3B (Q4 FY26)↑vs $57.0B (Q3 FY26)

  What this measures

  Data center segment revenue, sequential Q-over-Q. Captures Blackwell Ultra ramp and the start of Vera Rubin sample shipments. Beat or miss against the $62B run-rate sets the slope for H2 hyperscaler capex; a miss flattens Huang's-Law trajectory and re-rates the whole AI hardware narrative.

• Open vs closed gap on SWE-Bench Pro (coding)

  Open +0.9↑vs Closed +6

  Threshold: Sustained open lead reshapes enterprise procurement

  What this measures

  Coding benchmark differential between top open-weight model (Kimi K2.6 at 58.6) and top closed model (GPT-5.4 at 57.7). Sustained open lead reshapes enterprise procurement because open weights run on-prem with predictable cost-per-token and no rate limits. The flip from closed +6 to open +0.9 is the inflection that makes self-hosting frontier-class AI a real procurement option this quarter.

• Sovereign AI commitments (count / aggregate $)

  8 / $80B+↑vs 5 / $50B+

  What this measures

  Count of named national AI infrastructure programs and aggregate forward commitments. Current set: UAE Stargate (1 GW), Germany National DC Strategy, France IA program, Mistral-Sweden, GMI Japan, IndiaAI, UK AI Growth Zones aggregating $38.5B, plus the Saudi-PIF AI commitment. Reflects de-Westernization of compute provisioning and creates new merchant-silicon demand outside the hyperscaler axis.

• PJM 2026/27 capacity auction price ($/MW-day)

  $329↑vs $29

  Threshold: 11x in 24 months — power is the new binding constraint

  What this measures

  Most recent PJM auction cleared at 11x the prior auction price, reflecting tightness in the capacity market driven by data-center load growth outpacing new generation build-out. Behind-the-meter generation is now mainstream; FERC compliance milestones in May-June will determine whether 2027 clearing prices repeat or normalize.

• Time-to-power, busiest US markets (months)

  36-48↑vs 30-42

  What this measures

  Months from new-load interconnection request to energization in the most constrained US power markets (Northern Virginia, Phoenix, Dallas-Fort Worth, Columbus). Lengthening despite grid investment because demand is outpacing transmission build-out by 2-3x. The constraint is no longer chips, capital, or land — it is electricity delivery.

• Cost-per-task, frontier reasoning model

  ~$0.05↓vs ~$0.08

  Falling cost expands workloads (Jevons), not contracts demand

  What this measures

  Median cost across the frontier-tier reasoning models for a benchmark complex task. The 38% drop reflects continued pricing pressure from open-weight competition and provider economies of scale. Falling cost expands the addressable workload set rather than contracting demand — this is the Jevons signature in AI inference.

• Custom silicon share of incremental AI compute

  ~30%↑vs ~22%

  Threshold: >35% materially compresses merchant GPU pricing

  What this measures

  Approximate share of newly deployed AI compute capacity using custom silicon (TPU, Trainium, MTIA, Maia, Granite Rapids AI) versus merchant silicon (NVIDIA, AMD). The 30% threshold is structurally important: at this share, merchant GPU pricing power begins to compress as customers gain credible alternatives. Past 35% the compression is material and re-rates merchant gross margins.

Each prediction is falsifiable, time-bounded, and tied to a specific signal we will watch. Future issues score these hit, miss, partial, or pending and build a public track record.

Specific catalysts that would change the read materially. Watching these tells us whether the thesis is strengthening or weakening.

• Apr 29 - May 6

  Q1 2026 hyperscaler earnings

  Capex direction signal that hits all four hyperscalers in eight days. Watch: aggregate revising higher, AI-segment margin disclosure, RPO commentary. Higher pushes the capex / revenue ratio past 6.0 (a lever threshold); lower is the first sign of ROI re-rating risk and tests prediction p3.

• Late May 2026

  NVIDIA Q1 FY27 earnings

  First disclosure on Vera Rubin ramp velocity, HBM4 supply, and custom-silicon competitive pressure. Watch: data-center revenue vs the $62B run-rate, gross margin trend, customer-concentration commentary. A miss flattens the doubling slope; a beat resets the H2 hyperscaler capex tail.

• May 2026

  Google I/O + Microsoft Build

  Frontier model and platform announcements that directly test prediction p1-2gw-customer-funded. Watch: any disclosed customer-funded compute commitment greater than 2 GW, RPO disclosures, agent-platform pricing. A 2 GW+ commitment scores p1 a hit before its June 30 deadline.

• Through Q2 2026

  HBM4 memory supply ramp

  Validation status at SK Hynix, Samsung, and Micron is the binding constraint on Vera Rubin shipments. Watch: yield or qualification slips at any of the three. A slip compresses the H2 2026 hyperscaler capex tail materially; a clean ramp protects it and keeps Huang's slope intact.

• April - June 2026

  FERC PJM compliance milestones

  Behind-the-meter generation materiality threshold takes effect, reshaping unit economics of large loads in the busiest US power market. Watch: FERC commentary on capacity attribution, ERCOT and MISO reactions. The outcome determines whether 2027 PJM clearing repeats the $329/MW-day or normalizes.