Early access — cascade metrics are real (derived from canonical token telemetry); the operator field is a curated seed. Learn more about the data
📊 SigRank Quarterly Report

Q1 2026

State of AI Operator Token Efficiency. Computed from live operator telemetry — 11 operators, 5 platforms.

Headline Findings

  1. 1.The median AI operator scores Υ 2, 41% below the top decile (Υ 3). (June 2026)
  2. 2.The top-ranked operator (MO§ES™) achieves Υ 566, 373.9× the median. (June 2026)
  3. 3.claude operators lead on yield, averaging Υ 115 vs. Υ 1 elsewhere. (June 2026)
  4. 4.Across all ranked operators, 18% of input tokens are served from cache on average. (June 2026)

Platform Breakdown

PlatformOperatorsAvg Yield (Υ)
claude5115
gemini22
multi12
pi21
chatgpt10

Methodology

Figures are computed from the SigRank Index — a privacy-preserving leaderboard ranking AI operators by token-cascade efficiency (Υ = cache_read × output / input²). Data is built from on-device, ed25519-signed token-telemetry snapshots. No message content is ever read or stored. Full methodology at /methodology.

Cite this report

“According to the SigRank Index (Q1 2026), The median AI operator scores Υ 2, 41% below the top decile (Υ 3).”

signalaf.com/research/q1-2026

License

This report is licensed under CC-BY-4.0. Attribution required — cite as shown above.