Open benchmarks
Benchmarks on real jobs, open to read. The method and rubric are published, every reference answer is computed by code, and the task set is held back so it cannot leak into training.
Hurdle builds benchmarks from your team’s real work, runs every model worth testing on them, and hands you the answer and the files.
Benchmarks written from real cases, graded line by line against a standard your people agree, and run on every model worth testing.
Benchmarks on real jobs, open to read. The method and rubric are published, every reference answer is computed by code, and the task set is held back so it cannot leak into training.
Your job, your cases, your reviewers’ standard. Every model runs it, and you keep the benchmark, the scores and the cost per task.
Real jobs packaged as sandboxes with a grader, built for model labs to train and evaluate on.
A fixed scope, your people on the rubric, and a benchmark that stays yours.
50 to 150 real examples of the job, with the answers your team accepted.
Each case becomes a task. Your reviewers agree, line by line, what a correct answer contains.
Each model runs every task three times. Lines are checked by code wherever the answer can be.
You get the report and the files. When a model worth testing ships, we run it again.
Tasks, rubric and grader as plain files. Run them in your own pipeline, with any model.
Which model to use for the job, or a clear statement that none is ready yet.
Each missed line sits next to the reply that missed it, so you see why, not just how often.
One page each time a model worth testing ships, with the new scores beside the old.
Open benchmarks on real jobs. The method and rubric are published, and every reference answer is computed by code.
No. There is nothing to log in to. You get a finished benchmark: the tasks, the rubric, the grader and the report, as files you keep and can run yourself.
Between 50 and 150 real cases of the job, the answers your team accepted for them, and one person who can say what a correct answer contains.
Every current model worth testing for the job: the large hosted models, the open-weight families, and models you could run on your own machines.
Yes. The files are plain JSON, and the runner works with Amazon Bedrock, any OpenAI-compatible gateway, or a model on your own hardware.
Only to the model providers you approve for the run. Nothing is published, and cases can be anonymised before they leave you.
Each benchmark is scoped with you, and the price depends on the number of cases and models. We say it in the walkthrough.