ettin-reranker-1b-v1

Name: ettin-reranker-1b-v1
Author: cross-encoder

by cross-encoder

State-of-the-art cross-encoder reranker matching its 1.5B teacher at 1B parameters

52Kdl/month

1Bparams

HuggingFace Run it on your own data, free

Identifiers

Model ID

cross-encoder/ettin-reranker-1b-v1

Feature URI

mixpeek://reranker@v1/cross_encoder_ettin_1b_v1

Deploy ettin-reranker-1b-v1

Single-tenant

Mixpeek has no managed extractor for this model. On a single-tenant deployment you upload the weights and a custom plugin serves them next to the rest of your pipeline.

Read the customer-hosted guide Talk to us about single-tenant

Overview

Ettin Reranker 1B is the flagship model in the Ettin reranker family (17M to 1B parameters), trained via pointwise MSE distillation from the mxbai-rerank-large-v2 teacher. Built on Ettin ModernBERT encoders, it matches the teacher's MTEB Retrieval score within 0.0001 nDCG@10 while being smaller and faster.

The Ettin family provides a reranker at every size class, letting you trade latency for quality. The 150M variant runs under 10ms per query-document pair on GPU; the 1B variant delivers maximum accuracy for quality-critical retrieval.

Architecture

ModernBERT encoder backbone (Ettin variant) with a cross-encoder classification head. Takes concatenated query-document input and outputs a relevance score. Trained via pointwise MSE distillation from mxbai-rerank-large-v2 on diverse retrieval datasets.

Mixpeek SDK Integration

// Reranking is a retriever STAGE in Mixpeek, not an ingest-time extractor.
// The rerank stage runs a cross-encoder inference service; the shipped default
// is BAAI/bge-reranker-v2-m3. Pointing it at ettin-reranker-1b-v1 means registering that
// model as a custom reranker plugin and naming it in feature_uri, which is an
// Enterprise path. Stage contract read from GET /v1/discovery/stages.
const retriever = await mx.retrievers.create({
  namespace_id: "my-namespace",
  retriever_name: "search-then-rerank",
  stages: [
    {
      stage_name: "candidates",
      stage_id: "feature_search",
      parameters: { limit: 100 },
    },
    {
      stage_name: "rerank_results",
      stage_id: "rerank",
      parameters: {
        inference_name: "BAAI__bge_reranker_v2_m3",
        query: "{{INPUT.query}}",
        document_field: "content",
        top_k: 10,
      },
    },
  ],
});