Live bake-offs · cloud + open models

Find & monitor the most efficient LLM for your task.

Describe it in plain English. We bake off every model on your data, crown the cheapest one that’s good enough, then re-test as new models ship — so you’re always on the best-value pick.

Try Triage tickets Extract invoices Moderate comments Summarize calls

Free first run · no sign-up · then we keep watching as new models ship

How it works

Four steps to a verdict you can defend

No eval to write, no leaderboard guesswork. You describe the job; we measure every candidate on your data, name a winner, and keep the answer honest as the market moves.

✍️
01

Describe the task

Plain English, plus a few labelled examples if you have them. Type it, say it, or upload a CSV.

02

Run the bake-off

Every candidate is graded on your data against an evaluation we build for your exact task.

⚖️
03

Get the verdict

The cheapest model that clears your quality bar, with the receipts — accuracy, cost, and the cases it missed.

📡
04

We keep watching

Re-tested as new models ship. The moment a cheaper one clears your bar, you hear about it. The watch is the product.

Sample verdict

This is what a verdict looks like

A real bake-off on a ticket-triage task: every model scored against your bar, and the cheapest one that clears it, crowned.

Verdict Ticket triage · 5,000/day
Llama 3.1 8B86%
Gemini Flash90%
Claude Haiku94%
GPT-4o97%
✓ VERDICT
Claude Haiku94% · cheapest that clears your 92% bar
$0.14/ 1k tasks
Monitoring on · re-checks every new model that ships
Why not a router or a leaderboard?

Not a router. Not a leaderboard. A verdict.

Three kinds of tool sit nearby — none of them tell you which model to use on your task. Modeljury does, and watches it.

Routers & gateways

Route per request

Switch models inside your stack — adding latency and lock-in, on generic benchmarks rather than your task.

Eval tools

You build the eval

Test on your data — but you write the evaluation, and you get a dashboard, not a decision.

Leaderboards

Generic rankings

Rank generic tasks, not yours. Cheapest per token isn’t the same as cheapest per task.

Where it pays off

High-volume, gradable work

The boring-but-expensive backbone tasks every team runs thousands of times a day — where a small open model often clears the bar at a fraction of the price.

Support / CXTicket triageClassification
Finance / APInvoice extractionExtraction
Trust & SafetyContent moderationClassification
Sales / RevOpsLead qualificationClassification
Legal / ProcureContract clausesExtraction
Pricing

A dollar to start. A dollar a task to stay current.

The first bake-off is free. After that it’s the price of a coffee — and monitoring, the part that keeps you on the cheapest model as the market moves, is just $1 per task.

◆ Subscription
$1/ month
Your account and your dashboard — run bake-offs, save evaluations, and see the week’s best models across every task.
  • Unlimited bake-offs on your own keys
  • Your evaluation library, saved & reusable
  • Weekly leaderboard — best model per task
  • Full reports & the accuracy-vs-cost chart
Start free →
First bake-off is free — no card, no sign-up.
★ Monitoring
+$1/ task / mo
Turn the watch on, per task.
Each monitored task gets its own dashboard and a standing re-test as new models ship — so you’re always on the cheapest one that still clears your bar.
  • Per-task monitoring dashboard, tracked over time
  • Auto re-test every time a new model launches
  • Alert the moment a cheaper model clears your bar
  • Cost-saved & accuracy history, exportable
See the dashboards →
Pay only for the tasks you choose to watch.

See full pricing & what’s included →

Your dashboards

Watch the verdict hold — or change

Every monitored task gets tracked over time, and your whole account rolls up into a weekly view of what won where.

Questions

Straight answers

Why not just ask an LLM which model is best?
Because a model can’t impartially judge models — its pick is shaped by training and commercial bias, and it answers from general reputation rather than your task. It hasn’t tested anything on your data and doesn’t know the cheaper model that shipped last week. Modeljury runs a real bake-off on your examples and grades the results. Evidence, not endorsement.
Why not just build this myself with a few API calls?
You can run a first bake-off in an afternoon. The hard part is everything after: an evaluation tailored to your task, grading without a costly LLM-judge, a catalog kept current as models ship weekly, compliance and self-hosting, and continuous re-testing. That ongoing watch — not the one-off script — is the product.
Isn’t the newest, biggest model just the best?
It’s usually the most expensive, not the best fit. For classification and extraction, a small open model often clears your bar at a fraction of the price. “Cheapest that’s good enough for this task” is the real question — and only a measurement on your own data can answer it.
What about my data and compliance?
Run on your own API keys or fully self-hosted, so your data never leaves your environment. Residency and compliance filters prune the candidates before cost is even considered.
Models change every week — won’t the answer go stale?
That’s exactly why monitoring is the core product. We re-run your evaluation as new models launch and alert you the moment a cheaper one clears your bar — for $1 per task.

See it on your own task

The cheapest model that clears the bar — and a watch that keeps you there.

Try it now →