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One prompt. Four answers. Read them together.

Model choice is usually guesswork dressed up as preference. Side-by-side turns it into something you can look at.

How it works

Four steps, no configuration screen.

1

Write the prompt once

One prompt, sent to every column at the same moment.

2

Read them in parallel

All four stream at once, so the comparison takes as long as the slowest model, not the sum of four.

3

Weigh cost against quality

Time to first token and exact spend sit under each column.

4

Pick a winner and carry on

Mark an answer best and the thread continues on that model with full context. Your votes also train Auto-Route.

Seats

2–4

Typical cost

About 9 credits per run

Best for

Choosing a model for a job you will repeat

The honest part

What it does and does not do.

Comparison is not something to do on every message. It earns its keep in four places: choosing a model for a repeated job, high-stakes single answers where one model being confidently wrong is expensive, calibrating whether a frontier model is worth its premium on your work, and re-testing after a lab ships something new.

One caution. Side-by-side shows you four answers; it does not tell you which is correct. Where you cannot evaluate the answer yourself, agreement between models is weak evidence — they share training data and share blind spots. Treat consensus as a smell test, not a proof.

Also in the workspace

The other tools.

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See it running.

The demo workspace shows this tool on sample data. No account, no card.

Open the demo