jina-reranker-m0
by jinaai
Multimodal reranker handling text, images, and mixed documents across 29 languages
jinaai/jina-reranker-m0mixpeek://reranker@v1/jina_reranker_m0_v1Overview
Jina Reranker M0 is the first production-grade multimodal reranker from Jina AI, handling text-to-text, text-to-image, image-to-text, and text-to-mixed-document reranking in a single model. Built on Qwen2-VL-2B-Instruct, it supports 29+ languages and up to 4K image resolution with dynamic patching.
On Mixpeek, Jina Reranker M0 serves as a universal second-stage reranker for any retrieval pipeline: whether the candidates are text documents, scanned pages, product images, or mixed content. Its 91.02 nDCG@5 on ViDoRe v1 makes it state-of-the-art for visual document reranking.
Architecture
Cross-encoder based on Qwen2-VL-2B-Instruct. 2.4B parameters. Dynamic image patching up to 4K resolution. Outputs relevance scores for text, image, and mixed-modality inputs. 29+ language support.
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 jina-reranker-m0 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 visual document reranking (91.02 nDCG@5 on ViDoRe v1)
- Text, image, and mixed-modality reranking in one model
- 29+ language support including CJK, Arabic, and European languages
- Dynamic 4K image resolution for high-detail document pages
- Code retrieval support (63.55 nDCG@10 on CoIR)
Use Cases on Mixpeek
Benchmarks
| Dataset | Metric | Score | Source |
|---|---|---|---|
| ViDoRe v1 (visual doc) | nDCG@5 | 91.02 | Jina AI, 2026: Model Card |
| BEIR (text-to-text) | nDCG@10 | 58.95 | Jina AI, 2026: Model Card |
| MIRACL (18 langs) | nDCG@10 | 66.75 | Jina AI, 2026: Model Card |
Performance
Common Pipeline Companions
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Specification
Research Paper
Jina Reranker M0
arxiv.orgBuild a pipeline with jina-reranker-m0
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