NneurometricTask Router
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Task Router

Tasks we’ve measured, ready to route.

Route your requests by task alias (e.g. taskrouter/<task-id>). Calls go to the model that fits your priority (cheapest, balanced or most accurate) among those that clear the task’s quality floor. Each task shows exactly what to send and what you get back. Your own tasks are detected in your traffic or defined from samples.

Don’t see your task? Tell us what you do today, the model and prompt you use, and a few real examples. We benchmark other models against your current one and email you the results. Meanwhile, keep calling your model through Task Router.

Describe your taskAsk the assistant
Methodology

How we measure

Every comparison uses the same task-specific process. Results are directional rather than a production SLA, and each task shows its sample, rubric, judge, limitations, and pricing provenance.

01

Freeze a dataset

We create and freeze a representative set of real task cases, so every model is graded on exactly the same work.

02

Define the rubric

A task-specific rubric spells out what counts as correct — and what counts as a failure — before any model runs.

03

Run every tier

Qualified candidates from all four tiers run on the frozen holdout and are scored by an LLM judge for comparable pass rates.

04

Join published pricing

Measured token profiles meet the latest available provider prices, with source and freshness shown so every estimate can be checked.