Model reference · open weights

mxbai-rerank-large

mxbai-rerank-large 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 2 variants 91k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What mxbai-rerank-large is

🍞 mxbai-rerank-large-v2 (a.k.a ProRank-1.5B) This is the large model in our family of powerful reranker models. You can learn more about the models in our blog post. We have two models: - mxbai-rerank-base-v2 - mxbai-rerank-large-v2 (🍞) The technical report is coming soon! 🌟 Features - state-of-the-art performance and strong efficiency - multilingual support (100+ languages, outstanding English and Chinese performance) - code support - long-context support ⚙️ Usage Using Sentence Transformers Install Sentence Transformers: Using mxbai-rerank 1. Install mxbai-rerank 2. Inference Performance Benchmark Results Latency measured on A100 GPU Training Details The models were trained using a three-step process: 1. GRPO (Guided Reinforcement Prompt Optimization) 2. Contrastive Learning 3. Preference Learning For more details, check our technical report and technical blog post. 🎓 Citation If you find our models useful, please consider giving a star and citation arXiv: blog post:

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)1.5B
Context32k tokens
Variants2
Runs withtransformers
Released2025-03-03
Popularity91k downloads / month
Likes145
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-large-v21.5BBF16~3.6 GBWeights ↗
mxbai-rerank-large-v1435MBF16~1 GBWeights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys mxbai-rerank-large for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (mxbai-rerank-large 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-large","input":"text to embed"}'

Details

Languages, data & research

Languages

af am ar as az be bg bn br bs ca cs cy da

Tags

transformers safetensors qwen2 text-generation sentence-transformers text-ranking af am ar as az be bg bn

Papers

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

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