Early access — cascade metrics are real (derived from canonical token telemetry); the operator field is a curated seed. Learn more about the data
🤖⚔️🤖 Throw Down

Manus ad Manum

Two operators. One cascade layer. Υ Yield, SNR, Leverage, Velocity, 10xDEV & blended cost — the data tells you not just who's ahead, but where and why.

Operator A
vs
Operator B
Mingi ChoeREFINER II · #3531.6KΥ Yield◆ Leads 100
  • Leverage · closed loop · 3.9K×
  • Υ Yield · leads 72× · 31.6K
  • Cost · cost leader · $0.43/1M
  • Velocity · fast · 8.1 o/i
  • Efficacy · strong · 1002.93
VS100
The FieldSEEKER I · #116442Υ Yield
  • Leverage · closed loop · 300×
  • Υ Yield · trails · 442
  • Cost · cost leader · $0.55/1M
  • Velocity · fast · 1.5 o/i
  • Efficacy · strong · 79.22
Raw shapeInput ↑Output ↑CR ↑CW ↑Total ↑Cost ↓Mingi ChoeThe Field↑ higher is better · ↓ lower is better (cost) — both reach outward when good
Metric shapeΥ Yield ↑Leverage ↑SNR ↑Velocity ↑10xDEV ↑Efficacy ↑$/1M ↓Op Ratio ↑Mingi ChoeThe Field↑ higher is better · ↓ lower is better (cost) — both reach outward when good
Not enough history yet — both operators need at least two snapshots to chart Υ Yield trajectory.
Mingi ChoeDataThe Field
Raw
569.7KInput29.8K
4.6MOutput44.0K
2216.4MCache-read8.9M
64.4MCache-write470.4K
2286.1MTotal9.5M
$0.43Cost$0.55
Metrics
31.6KΥ Yield442
89.1%SNR59.6%
3.9K×Leverage300×
8.13Velocity1.47
3.5910xDEV2.48
$0.43Cost per 1M$0.55
1002.93Efficiency79.22
3890:1:8.1Op Ratio300:1:1.5
2286.1MTotal9.5M
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