YOUR AINEEDS AQUALITYSTANDARD
TRUSTED BY TEAMS BUILDING AI
Picnic
THE GOLD STANDARDFOR YOUR AI QUALITY
HIGHER QUALITYLOWER COST
BENCH COMPARISONS
What actually works
on real work.
BENCH takes a real job a business runs on AI, writes down the rules it has to meet, and puts every model and every setup through it. Then it publishes what each one got right, what it got wrong, and what it costs to run.
13 SETUPS TRIEDThe setup BENCH found
- Model
- GPT-OSS 120B
- Prompt
- Your own rules, written out in full
- Tools
- None needed for this job
- Harness
- One pass per case, no retries
Gets right
38 of 39
Costs
$1 per 1,000
HOW TO BENCH IT:
- CONNECT YOUR CODEBASE
BENCH maps your prompts, harness, tools & models
Run your real AI system against what good means
- KEEP IMPROVING
Watch production, catch failures, bench again
- SHIP BETTER AI
Prove the quality, then cut what it costs
SHIP QUALITY CONTINUOUSLY
Whole AI system · Run #042OVERALL BENCH SCORE
65/100
One score for your whole AI system, measured against your quality standard. This is your AI today, before benching.
WHY THE SCORE IS 65
×Refund policy accuracy12 failures
×Plan confirmation7 failures
×Vague instruction“Be as helpful as possible.”
×Overpaying on every requestSonnet costs ~4x more than GPT-5.4 mini
QUESTIONS
BENCH tests the whole AI system you ship, not just the prompt, it reads your codebase, works out what a good answer means for your business, runs real work through the system, and tells you which setup does the job and what it costs
Your coding agent does it, install BENCH in your project and point it at the repo, it finds the AI systems you already have, the prompts, the models, the tools they call and the harness around them, and sets up the tests, no new platform to learn
Because that is not what fails, a wrong answer can come from the prompt, from what the system was allowed to look up, from how many turns it got or from the model, BENCH changes one of those at a time so you know which one to fix
A cheap model that scores badly is usually making one mistake over and over, BENCH finds it, fixes it, and proves the cheap setup now does the job, that is often the same result for a fraction of the bill
Nothing is recommended on a hunch, every change is scored on the same frozen cases as the original, failures are shown next to the wins, and your team sees the evidence before anything ships
Yes, BENCH watches what happens in production, spots new failures, adds them to the tests, re-runs everything and prepares the next fix as your product and the models change
