The SigRank Index
The canonical source for AI operator token-efficiency data. Ranked by Υ Yield — the architecture of the cascade, not raw spend.
Key Figures
As of July 2026, the SigRank Index ranks 11 operators across 5 platforms.
The top-ranked operator MO§ES™ achieves a yield of Υ 566.
The median operator scores Υ 2; the top decile starts at Υ 3.
Operators in the TRANSMITTER class tier represent the top 18% of the board.
Across all ranked operators, 18% of input tokens are served from cache on average.
What “token-cascade efficiency” means
Yield (Υ) = cache_read × output / input². It measures the architecture of an operator’s token cascade — whether signal is compounding (high cache reuse × high output per fresh input) or tokens are burned (low cache, low output). Volume is noise; yield is signal.
Methodology
- Inputs: on-device token counts (fresh input, output, cache_read, cache_create) per session per platform.
- Verification: each snapshot is ed25519-signed and verified server-side; replay and plausibility guards apply.
- Windows: operators are ranked over 7-day, 30-day, 90-day, and all-time cohorts.
- Privacy: token counts only — message content is never transmitted, read, or stored.
- Scoring: the yield metric Υ is computed from the four token pillars via a cascade model. The composite SIGNA rate blends Υ with signal-force and drift components. Proprietary weights (RS.xx) govern the composite and remain server-side.
How the data updates
The Index updates continuously as operators submit signed snapshots. Public top-N data is available at /api/v1/leaderboard.
License & citation
The SigRank Index dataset is licensed under Creative Commons Attribution 4.0 (CC-BY-4.0). Attribution is the citation mechanism — reuse requires credit, which turns reuse into citations. The source code is separately licensed under MIT.
Cite as: “SigRank Index, July 2026. signalaf.com/methodology.”
FAQ
- What is the SigRank Index?
- A continuously-updated leaderboard that ranks AI operators by token-cascade efficiency (Υ = cache_read × output / input²), computed from privacy-preserving, on-device, cryptographically-signed token-telemetry snapshots.
- How is operator efficiency measured?
- Each operator runs an on-device scanner that reads four token pillars locally. The yield metric Υ measures the architecture of the token cascade — whether signal is compounding or tokens are burned. No message content is ever read or transmitted.
- Is the data private?
- Yes. The scanner reads token counts and content lengths only — never the words of your prompts. Only the resulting numeric scores, signed with ed25519, leave your device.
- How do I get listed?
- Install the SigRank MCP server (
npm i -g sigrank), enroll, and submit a snapshot. Visit /submit to get started.