live TPS, latency, and failure rate — the metrics the SI dashboard doesn't show.
The Surplus Intelligence marketplace exposes pricing, liquidity, and 24h volume for each model — but not TPS, wall-clock latency, or per-provider failure rates. So we measure them ourselves. Every request routed through surp feeds this board, and the resulting health scores feed back into routing: cheap-and-flaky loses to slightly-pricier-but-reliable.
why this matters: A model listed at $0.01/M with 50 active offers might still be the wrong choice if it 500s half the time or takes 8 seconds to respond. Price is one signal; reliability is another. This board makes both visible.
composite health ranking
Models are ranked by a composite 0-100 score: reliability (60%) × speed (30%) × throughput (10%). Green ≥ 70, amber 40-69, red < 40.
#
model
health
requests
failures
failure rate
p50 latency
p95 latency
mean latency
TPS
tokens
No routing samples yet. Health scores populate as requests flow through the gateway.
methodology
Window: rolling 1 hour (configurable via SURP_HEALTH_WINDOW).
TPS: requests / elapsed window seconds.
p50/p95: percentile of successful-request latencies (interpolated).
Failure rate: non-ok responses / total responses.
Health score:(1 - failure_rate) × 60 + speed_norm × 30 + min(1, TPS) × 10, where speed_norm = (2000 - p50) / 1950 clamped to [0,1].
Pruning: samples older than 24h are deleted automatically.
free-to-paid conversion
How many free-tier users have upgraded to a paid combo, and which one they chose. This is the metric that tells us whether the free tier is doing its job — bootstrapping usage — without permanently subsidizing freeloaders.
3
distinct free users
0
upgraded to paid
0.0%
conversion rate
0
free requests today
top paid combos chosen by free users
paid combo
conversions
No conversions recorded yet.
what this enables
Smarter free routing: the free pool can prefer reliable models, not just the absolute cheapest.
Provider accountability: sellers who degrade get visible — not hidden behind a static offer count.
Capacity planning: TPS trends reveal which providers are scaling and which are stagnating.
Community good: this data doesn't exist anywhere else. We can publish it as a public good.