How Framer ensures high-quality translations

Framer translates user-generated content into more than 200 languages. To make that work reliably across real websites, models are evaluated not just for language quality, but for how well they handle structured content and product-specific rules.

Why website translation is different

Website content is rarely just plain text. Pages often include structured elements that must stay valid after translation — such as HTML markup, glossary terms, custom instructions, and URL paths. A model may produce fluent results for plain text but still introduce issues when these constraints are present. Framer evaluates models specifically for how reliably they handle these real-world scenarios.

Glossary rules and consistent terminology

Framer’s localization glossary lets you define how specific terms should appear in each language. This keeps brand names, product terminology, and technical phrases consistent across your site.

Glossary rules can include:

• Fixed translations for specific languages

• Case-sensitive replacements

• Terms that should never be translated

For example, a glossary rule might require a phrase to always use a predefined translation while preserving its original casing:

Preserving HTML structure

Many pages include HTML elements such as links, formatting tags, or embedded components. These structures must remain valid after translation so the page continues to render correctly.

Framer evaluates models using inputs that contain HTML markup and verifies that the translated output preserves the correct structure. This helps prevent broken links, missing tags, or malformed content.

Handling localized page paths

When pages are localized, their URLs may also need to be translated. Translated paths must follow valid slug formatting rules so links stay consistent and predictable across languages.

Framer evaluates translation models to ensure localized paths:

• Follow the allowed slug format

• Avoid invalid characters

• Remain readable in the target language

How Framer evaluates translation models

Framer continuously tests translation models against a representative set of languages and real-world content scenarios from Framer projects. Models are evaluated across four key areas:

• Translation quality across different languages

• Reliability when handling structured content such as HTML and glossary rules

• Speed, so translations appear quickly in the localization interface

• Cost, which affects how efficiently translations can be delivered at scale

Only models that perform well across all four criteria are used in Framer. See our blog post on how we evaluate translation models for a detailed breakdown.

Continuous improvements

AI translation technology evolves quickly. Framer regularly evaluates new models to determine whether they improve quality or reliability. When a model demonstrates better performance without compromising structured content handling, it may be adopted to improve localization results across the platform.