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Compare model responses

Compare LLM Reasoning

Give several models the same question and context. Compare the assumptions they make, the objections they raise, and how their answers change after review.

The Problem

A leaderboard cannot answer your question.

Compare responses on the work you actually need to assess.

What benchmarks leave out

Benchmarks summarize performance on fixed tasks. They cannot show how a model will respond to your documents, constraints, or review instructions.

What a direct comparison shows

Give available models the same case and inspect their responses in one record. The comparison is specific to that review; it is not a general model ranking.

Illustrative example: comparing the assumptions

Illustrative review
Example
User Premise

"The car wash is 100m away. Should I walk or drive there?"

GGemini 3.1 Pro (Flawed Reasoning)

"You should walk to save emissions and get some exercise. It's only 100m!"

DDeepSeek V4 Pro (Superior Reasoning)

"I strongly disagree. This treats the question as a pure transportation optimization problem. If you walk, the car sits unwashed. The correct answer is unequivocally drive."

Claude Opus 5C

"The Challenger correctly identified the premise's trick. The user needs the car at the destination to utilize the service. A car wash cannot wash a pedestrian."

OGPT-5.6 Sol (Chairman)

"Consensus reached. While the initial response prioritized safety and emission conditioning, it failed basic logical constraints. You must drive to get the car washed."

Core Features

Built for consequential work

Surface unsupported claims

Independent model responses can surface contradictions, missing support, and claims that need external checking before you rely on them.

Use independent perspectives

Assign different roles and review paths so a draft faces more than one perspective. Agreement remains a signal to inspect, not a guarantee of truth.

Inspectable review records

Keep the transcript of the review, including its objections and conclusion, so you can inspect the reasoning and decide what still needs human verification.

How a review works

Bring the work, choose the kind of feedback you need, and inspect the result.

01

Add the work

Paste a proposal, plan, claim, or AI answer. Include the question and context the reviewers need.

02

Choose the review

Select models, a review format, and the number of rounds. Follow their responses as the review runs.

03

Read and revise

Read the conclusion, unresolved objections, and transcript. Revise the work and check the evidence that matters.

Published research

Agreement is useful evidence, not proof of accuracy.

Our observational disagreement study examines 558 completed reviews and 9,507 assessed claims in the product corpus. It describes how model positions changed; it is not an accuracy benchmark.

Read the study →

Compare responses to your own question.