Every claim, checked
against six models.

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.

Start free

20 credits free, no card. Then $5 for 100 credits, and they never expire. There is no subscription.

OpenAI
OpenAIGPT-5
Waiting…
Claude
AnthropicClaude Sonnet 5
Waiting…
Gemini
GoogleGemini 3.7 Flash
Waiting…
DeepSeek
DeepSeekDeepSeek V4 Pro
Waiting…

The same prompt, five image models.

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.

GPT-5 Image rendering the same corner bakery prompt
OpenAIGPT-5 Image1024×1024 · 1 cr
GPT-5 Image Mini rendering the same corner bakery prompt
OpenAIGPT-5 Image Mini1024×1024 · 1 cr
Nano Banana Pro rendering the same corner bakery prompt
GeminiNano Banana Pro1408×768 · 5 cr
Nano Banana 2 rendering the same corner bakery prompt
GeminiNano Banana 21408×768 · 3 cr
Nano Banana 2 Lite rendering the same corner bakery prompt
GeminiNano Banana 2 Lite1408×768 · 2 cr

Five renders, one run

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 prompt

The verdict, claim by claim.

Keimodel 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.

0agreement
FactualPartial consensus

Mostly aligned, but one date is contested.

Synthesized from 4 models

GPT-5Claude Sonnet 4.6Gemini 3.5Llama 3.3

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

  • The treaty ended the Thirty Years' War
  • It established state sovereignty norms

Where they diverge

The signing month

October
GPT-5Claude Sonnet 4.6
May
Llama 3.3

Claim agreement

Signed in 1648

GPT-5Claude Sonnet 4.6Gemini 3.5Llama 3.3

Signed in October 1648

GPT-5Claude Sonnet 4.6Gemini 3.5Llama 3.3

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.

You pay for questions you ask. That is the whole model.

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

Priced before you run

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.

Or bring your own key

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.

What to ask six models.

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.

Judgment calls

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?

Predictions

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?

Edge cases

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?

Fast-moving facts

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?

Powered by every leading AI provider

OpenAIOpenAI
GPT-5GPT-5 MiniGPT-5 ProGPT-4oGPT-4o Mini
AnthropicAnthropic
Claude 4 OpusClaude 3.7 SonnetClaude 3.5 Haiku
GoogleGoogle
Gemini 2.5 ProGemini 2.5 FlashGemini 2.0 Flash
MetaMeta
Llama 4 MaverickLlama 4 ScoutLlama 3.3 70B
MistralMistral
Mistral LargeMistral SmallCodestral
DeepSeekDeepSeek
DeepSeek V3DeepSeek R1
GrokxAI
Grok 3Grok 3 Mini
QwenQwen
Qwen 3 235BQwen 3 32B
PerplexityPerplexity
Sonar ProSonar

Go beyond the chat

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Guides, explainers, benchmark deep dives, and practical how-tos, built around the models you compare.

How-to

How to instrument LLM apps with OpenTelemetry

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.

6 min readRead →

Ask the question you have been guessing at.

Six 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.

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