Model reference · open weights

mxbai-rerank-xsmall

mxbai-rerank-xsmall is an open-weight embedding model from mixedbread-ai, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.

Embeddings mixedbread-ai 1 variants 580k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What mxbai-rerank-xsmall is

mxbai-rerank-xsmall-v1 This is the smallest model in our family of powerful reranker models. You can learn more about the models in our blog post. We have three models: - mxbai-rerank-xsmall-v1 (🍞) - mxbai-rerank-base-v1 - mxbai-rerank-large-v1 Quickstart Currently, the best way to use our models is with the most recent version of sentence-transformers. pip install -U sentence-transformers Let's say you have a query, and you want to rerank a set of documents. You can do that with only one line of code: Install transformers.js npm i @xenova/transformers Let's say you have a query, and you want to rerank a set of documents. In JavaScript, you need to add a function: Using API You can use the large model via our API as follows: The API comes with additional features, such as a continous trained reranker! Check out the docs for more information. Evaluation Our reranker models are designed to elevate your search. They work extremely well in combination with keyword search and can even outperform semantic search systems in many cases. The reported results are aggregated from 11 datasets of BEIR. We used Pyserini to evaluate the models. Find more in our blog-post and on this spreadsheet. Community Please join our Discord Community and share your feedback and thoughts! We are here to help and also always happy to chat. Citation License Apache 2.0

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

Makermixedbread-ai
TypeEmbedding models
Parameters (lead)71M
Context512 tokens
Variants1
Runs withtransformers
Released2024-02-29
Popularity580k downloads / month
Likes58
LicenceOpen weights

How it works

How embedding models work

Your textsentence / documentEncodermaps meaningVectorlist of numbersAn embedding model turns text into a vector, so similar meanings sit close together — the basis of search and RAG.

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

VariantParamsPrecisionVRAMFits 16 GBWeights
mxbai-rerank-xsmall-v171MBF16~0.2 GBWeights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys mxbai-rerank-xsmall for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (mxbai-rerank-xsmall below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/embeddings \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"mxbai-rerank-xsmall","input":"text to embed"}'

Details

Languages, data & research

Languages

en

Tags

transformers onnx safetensors deberta-v2 text-classification reranker transformers.js sentence-transformers text-ranking en text-embeddings-inference endpoints_compatible

Licence

Open weights

Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗

Sources

Weights & code

Want mxbai-rerank-xsmall on EU-owned hardware?

Request this model on EU hardware See what’s served now

Explore

More embedding models

© 2026 AxForge · EU-hosted AI infrastructure Pricing Docs Trust Privacy Terms