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
import { Mixpeek } from "mixpeek";
const mx = new Mixpeek({ apiKey: "API_KEY" });
// Managed: create a collection over a bucket; Mixpeek runs this model's extractor
const collection = await mx.collections.create({
namespace_id: "my-namespace",
collection_name: "my-collection",
source: { type: "bucket", bucket_ids: ["bkt_your_bucket"] },
feature_extractor: {
feature_extractor_name: "multimodal_embedding",
version: "v1",
parameters: { model_id: "jinaai/jina-embeddings-v5-omni-small" },
},
});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
Specification
Research Paper
Jina Reranker M0
arxiv.orgBuild a pipeline with jina-reranker-m0
Add this model to a processing pipeline alongside other extractors. Combine with retrieval stages for end-to-end search.
Run on your data