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# How Roblox Uses AI to Translate 16 Languages in 100 Milliseconds

**[ByteByteGo](https://daily.dev/sources/bytebytego)** · 10 min read · 2 upvotes · 1 comments

## Summary

Roblox built a single unified transformer-based translation model using Mixture of Experts (MoE) architecture to handle all 256 language direction pairs across 16 languages, replacing the need for 256 separate models. To meet a 100ms latency ceiling at 5,000+ chats per second, they applied knowledge distillation to compress the model from ~1B to under 650M parameters, combined with quantization and model compilation. The serving pipeline includes a translation cache, dynamic batching, and an embedding cache that avoids re-encoding the same source message for multiple target languages. For quality measurement, they built a reference-free quality estimation model that scores translations at word-level granularity without needing human reference translations. Low-resource language pairs were improved via iterative back-translation, and domain-specific slang was handled through human-labeled platform terminology.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://blog.bytebytego.com/p/how-roblox-uses-ai-to-translate-16>

## Community discussion

Top comments from developers on daily.dev.

**@bobbyiliev** · 0 upvotes

> great read!

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