Ask once and Keimodel runs your question across up to six models, then returns one answer broken into claims, each marked with the models that back it and the models that dispute it.
20 credits free, no card. Then $5 for 100 credits, and they never expire. There is no subscription.
Give two image models the same words and they rarely picture the same scene. Switch to Image mode and Keimodel runs one prompt across all five at once, so you choose the frame instead of paying five times over to find it.
Create an image of a corner bakery at dawn, warm light spilling onto a wet street, shot on 35mm film.





We ran these on 1 September 2026: one prompt, one run, the first result from each model, no retries and no edits. Two came back square and three came back widescreen from the same words, which is the reason to look at them side by side.
All five cost 12 credits together, about $0.48 on the $20 bundle.
Run your own promptKeimodel reads every response and merges them into one answer, then splits that answer into its individual claims. Each one carries the models that support it and the models that dispute it, so a line every model backed and a line one model invented never look the same on the page.
Synthesized from 4 models
Consensus answer
The treaty was signed in 1648, ending the Thirty Years' War. Most models agree on the year; the disagreement is over the exact month.
Where they agree
Where they diverge
The signing month
Claim agreement
Signed in 1648
Signed in October 1648
Llama places it in May, likely a hallucinated month.
Worth saying plainly: models that agree are not independent witnesses. They share training data and increasingly learn from each other, so they can converge on the same mistake. Six models disagreeing is a reliable signal to go look. Six models agreeing is weaker evidence than it feels like, and Keimodel is built to show you the first rather than sell you the second.
No plan, no seat, no monthly minimum, nothing to cancel. You buy credits once and they never expire, every model shows its cost before you run it, and we refund any run that does not finish.
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1 credit = 1 model response · Most models cost 1-5 credits · The verdict is priced separately
Every model carries its credit cost in the picker and its real input and output price per million tokens on the panel, and the total for the lineup you have built sits under the Run button. We meter nothing after the fact.
Add an OpenRouter key in Settings and every model response runs on your own account and costs you no credits at all. Only the verdict, the part that reads them all and marks up the claims, stays on ours.
Not every question. Ask one with a settled answer and all six agree, the confidence score reads high, and you have learned something small. The questions worth the credits are the ones where the models pull apart, and you can spot those by their shape rather than by their subject.
Real tradeoffs, no single right answer. Models weight the tradeoffs differently and you get to see how.
Should we move a write-heavy service off Postgres to DynamoDB, or shard what we have?
Nothing to look up, so each model reasons from a different prior. The spread is the useful part.
What breaks first if traffic on this architecture grows tenfold?
The place a confident single answer is most likely to be quietly wrong, and the place a dissenting model earns its keep.
How does a rounded tax total behave when line items are discounted after tax?
Models train on different snapshots of the world, so on anything recent they know different things.
What changed in EU AI Act enforcement obligations this year?
Playbooks for your job, guides for every workflow, and open models you can run yourself. The library behind the chat.
Copy-paste prompt playbooks for your exact job, from real estate to bookkeeping.
Step-by-step guides for running, building, and shipping with LLMs and agents.
Run open models on your own machine. Private, offline, and free to run.
Guides, explainers, benchmark deep dives, and practical how-tos, built around the models you compare.
OpenTelemetry (OTel) is the vendor-neutral standard for distributed tracing. The GenAI semantic conventions extend it to LLM calls. This guide covers setting up OTel tracing for LLM applications, exporting to Jaeger or Grafana, and the GenAI conventions.
LLM API costs can grow unexpectedly as usage scales. This guide covers cost attribution, per-request tracking, anomaly detection, and practical techniques that reduce costs by 50-80% without sacrificing quality.
5 min readPromptfoo is an open-source CLI for testing, evaluating, and comparing LLM prompts. This guide covers writing test cases in YAML, running evaluations, comparing models, and catching prompt regressions in CI.
6 min readLangSmith is LangChain's observability platform for logging, tracing, and evaluating LLM applications. This guide covers setup, automatic tracing, custom traces, and using the dashboard to debug production issues.
6 min readSix models, one answer, and a line under every claim saying who backed it. Your first 20 credits are on us, and there is nothing to cancel afterwards.