cross-encoder AI Models

Approved models

23

Records published from this collection

Provider information

lab

Review approach

Verify each model’s source, terms, capabilities, and current availability

cross-encoder models in this directory cover text ranking, zero-shot classification. Start with the task you need to solve, then open a model profile to check its recorded inputs, outputs, licensing and deployment options.

Models to explore

Choosing a model

Evaluate the reranker on the candidates your first-stage retriever actually returns. Compare nDCG, relevant results near the top, batch throughput and tail latency; a reranker cannot recover documents the retriever never supplied.

Compare the right details

Check whether two entries describe distinct models or different hosted routes for the same model. Keep the checkpoint, host, test settings and evaluation date together. Missing prices and limits mean the directory has no recorded figure, not that use is free or unlimited.

Browse the AI model directory or compare two models.

cross-encoder model list

Review each record individually; collection membership does not imply a recommendation or guarantee of availability.

23 models
cross-encoder/ettin-reranker-32m-v1
cross-encoder
5.0————
cross-encoder/mmarco-mMiniLMv2-L12-H384-v1
cross-encoder
5.0————
cross-encoder/ms-marco-electra-base
cross-encoder
5.0————
cross-encoder/ms-marco-MiniLM-L12-v2
cross-encoder
5.0————
cross-encoder/ms-marco-MiniLM-L2-v2
cross-encoder
5.0————
cross-encoder/ms-marco-MiniLM-L4-v2
cross-encoder
5.0————
cross-encoder/ms-marco-MiniLM-L6-v2
cross-encoder
5.0————
cross-encoder/ms-marco-TinyBERT-L2
cross-encoder
5.0————
cross-encoder/ms-marco-TinyBERT-L2-v2
cross-encoder
5.0————
cross-encoder/ms-marco-TinyBERT-L6
cross-encoder
5.0————
cross-encoder/nli-deberta-v3-base
cross-encoder
5.0————
cross-encoder/nli-deberta-v3-large
cross-encoder
5.0————
cross-encoder/nli-deberta-v3-small
cross-encoder
5.0————
cross-encoder/nli-deberta-v3-xsmall
cross-encoder
5.0————
cross-encoder/nli-distilroberta-base
cross-encoder
5.0————
cross-encoder/nli-MiniLM2-L6-H768
cross-encoder
5.0————
cross-encoder/qnli-electra-base
cross-encoder
5.0————
cross-encoder/quora-distilroberta-base
cross-encoder
5.0————
cross-encoder/quora-roberta-base
cross-encoder
5.0————
cross-encoder/stsb-distilroberta-base
cross-encoder
5.0————
cross-encoder/stsb-roberta-base
cross-encoder
5.0————
cross-encoder/stsb-roberta-large
cross-encoder
5.0————
cross-encoder/stsb-TinyBERT-L4
cross-encoder
5.0————

1–23 of 23 models · select a column to sort

About this order: Recommended shows our editorial shortlist first, followed by recent releases. The spec score is a 0–100 figure SyncDev calculates from each vendor's published specifications — context window, reasoning support, input modalities, tool calling, maximum output and how recently the model shipped. It measures breadth of capability, not benchmark performance, so a higher-scoring model is not automatically the better choice for your task.

About cross-encoder models

It groups source-backed directory records for research and comparison. Review each model page and its primary documentation because collection membership alone does not prove quality, availability, or suitability.