ettin-reranker-1b-v1
by cross-encoder
State-of-the-art cross-encoder reranker matching its 1.5B teacher at 1B parameters
cross-encoder/ettin-reranker-1b-v1mixpeek://reranker@v1/cross_encoder_ettin_1b_v1Overview
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,
},
},
],
});Capabilities
- SOTA reranking at 1B parameters on MTEB Retrieval
- Family of 6 sizes (17M-1B) for latency/quality tradeoffs
- Matches 1.54B teacher within 0.0001 nDCG@10
- Compatible with any first-stage retriever
- Apache 2.0 license
Use Cases on Mixpeek
Benchmarks
| Dataset | Metric | Score | Source |
|---|---|---|---|
| MTEB Retrieval (eng, v2) | nDCG@10 | ≈teacher (0.0001 gap) | Ettin blog, May 2026 |
| NanoBEIR (13 datasets) | nDCG@10 | SOTA at 1B | Ettin blog, May 2026 |
Performance
Common Pipeline Companions
Specification
Research Paper
Introducing the Ettin Reranker Family
arxiv.orgBuild a pipeline with ettin-reranker-1b-v1
Add this model to a processing pipeline alongside other extractors. Combine with retrieval stages for end-to-end search.
Run it on your own data, free