The numbers
we build on.
Choosing the wrong model makes an automation slow, expensive, or both. We keep the benchmark, pricing and latency data our own builds depend on in one place — gathered from independent sources we trust, and checked against what we see running these models in production.
What’s in the Lab
Reference data we keep open in a tab, published for anyone who needs the same answer.
How we source this
Worth being blunt about, because it changes how much you should trust it.
Gathered, not generated
The benchmark and pricing figures come from established independent sources. We don’t run these benchmarks ourselves and we don’t present their work as ours — every source is named and linked on the page it appears.
Checked against real builds
Where we’ve run a model inside a client workflow, we say what we actually saw: latency under load, cost per run, and where quality held up or didn’t.
Refreshed, not retyped
We pull each dataset straight from its source on a schedule and show you when it last updated — so it reflects current prices and current models, never a table we typed out once and forgot.
Skip the comparison — we’ll pick the model
Every workflow we build is costed and benchmarked before it ships, so you get the cheapest model that actually holds up.