Published event
ArtificialIntelligence OpenSourceRelease 1 source(s)

Introducing the Ettin Reranker Family

Updated September 26, 2026 · 2:44 PM · source date May 19, 2026

Summary

Introducing the Ettin Reranker Family Introducing the Ettin Reranker Family Published May 19, 2026 Update on GitHub Upvote 58 Tom Aarsen tomaarsen TL;DR Today I'm releasing six new Sentence Transformers CrossEncoder rerankers, state-of-the-art at their respective sizes, built on top of the Ettin ModernBERT encoders, together with the data and full training recipe that produced them: cross-encoder/ettin-reranker-17m-v1 cross-encoder/ettin-reranker-32m-v1 cross-encoder/ettin-reranker-68m-v1 cross-encoder/ettin-reranker-150m-v1 cross-encoder/ettin-reranker-400m-v1 cross-encoder/ettin-reranker-1b-v1 The models were trained with a distillation recipe : pointwise MSE on mixedbread-ai/mxbai-rerank-large-v2 scores over cross-encoder/ettin-reranker-v1-data , which is a subset of lightonai/embeddings-pre-training mixed with a reranked subset of lightonai/embeddings-fine-tuning . Our six rerankers paired with google/embeddinggemma-300m on MTEB(eng, v2) Retrieval.

Why it matters

This OpenSourceRelease is relevant to the technology intelligence record because it involves GitHub, Google, Apple, NVIDIA. The source article should remain the factual reference for follow-up coverage.

Key facts
  • Introducing the Ettin Reranker Family Published May 19, 2026 Update on GitHub Upvote 58 Tom Aarsen tomaarsen TL;DR Today I'm releasing six new Sentence Transformers CrossEncoder rerankers, state-of-the-art at their respective sizes, built on top of the Ettin ModernBERT encoders, together with the data and full training recipe that produced them: cross-encoder/ettin-reranker-17m-v1 cross-encoder/ettin-reranker-32m-v1 cross-encoder/ettin-reranker-68m-v1 cross-encoder/ettin-reranker-150m-v1 cross-encoder/ettin-reranker-400m-v1 cross-encoder/ettin-reranker-1b-v1 The models were trained with a distillation recipe : pointwise MSE on mixedbread-ai/mxbai-rerank-large-v2 scores over cross-encoder/ettin-reranker-v1-data , which is a subset of lightonai/embeddings-pre-training mixed with a reranked subset of lightonai/embeddings-fine-tuning .
  • Our six rerankers paired with google/embeddinggemma-300m on MTEB(eng, v2) Retrieval.
  • See Results for five more embedder pairings.
  • If you're new to rerankers and want the "why" first, jump to What is a reranker, and why pair one with an embedder?
  • If you just want to plug a model in, jump to Usage .
  • If you want to train your own, jump to Training .
Entities in this story
Related events