Compare Engines

Test the same content through two engine configurations to evaluate a change before committing.

The workflow#

"Compare our production engine against the staging engine on these 5 strings for Japanese"

What happens:

1. The assistant localizes the content through both engines
2. Presents results in a side-by-side table
3. Highlights differences: "The staging engine applies the new glossary term for 'onboarding' (オンボーディング) while production still uses the descriptive localization (導入手続き)"

When to use this#

• After tuning — verify the change improved output before promoting
• Evaluating model changes — same config, different primary model
• Testing glossary impact — with and without new terms
• Comparing engines for different use cases — marketing vs. technical content

Example comparisons#

Before/after a tune#

"Localize 'Welcome to your new workspace' to German through engine A and engine B"

Shows whether the glossary entry for "workspace" is being preserved in the updated engine.

Model evaluation#

"I switched the Japanese model from GPT-4.1 to Claude Sonnet. Compare outputs for these 10 UI strings."

Side-by-side reveals which model handles short UI strings vs. longer descriptions better for your specific domain.

Glossary depth testing#

"Compare the engine with our full 200-term glossary against a fresh engine with no glossary on these legal strings"

Quantifies how much the glossary contributes to output quality for a specific content type.