Miatz playground

Cost & Latency Bench

Watch a demo's pennies turn into a production cost cliff.

Coming to the Build-LabAIE-402BYOK AIAI-Coredev · data
The Demystify signature

The '1000x' extrapolation slider is the reveal — a $0.02 demo run becomes a visible $4,000/day line the moment the learner drags one slider, making the hidden unit-economics cliff impossible to unsee.

How it works

What goes in, what comes out

What it does

Learner fires the identical task at several models simultaneously and watches a synchronized race-bar animation of token-by-token streaming speed next to a live-rising cost odometer, reading real numbers off the platform's own cost meter rather than a spec sheet. A '1000x' slider then extrapolates that single run's cost and latency to a chosen production scale (requests/day), turning invisible unit economics into a visible cliff the learner has to decide whether to ship past.

You bring

A representative task/prompt, a quality bar it must clear, and a target production request volume.

You get

A live latency race animation, a rising cost odometer per model, an extrapolated daily/monthly cost-at-scale chart, and a recommended routing/caching strategy under the quality floor.

You control

Model set to race, requests/day extrapolation slider, caching on/off, routing strategy (cheapest-that-passes vs. fixed model), and a quality floor (minimum eval score) the routing must respect.

Where it's used

Read-only intro in Core Foundation F6 (Tools, Keys & Cost Literacy); full in-module lab for AIE-402 (COULD tier, Operator badge).

routing & cachingcost-attribution dashboardstoken-level latencyfp16/int8/int4 quality-deltaunit economics at scale

Concepts click when you open the machinery.

Three labs are already live and free — the same hands-on style this playground brings to its module.