---
title: jinaai/jina-colbert-v2 (Encode)
description: Trained by Jina AI.. XLM-RoBERTa, 559M parameters.
canonical_url: https://superlinked.com/models/jinaai-jina-colbert-v2--encode
last_updated: 2026-05-25
---

# jinaai/jina-colbert-v2 (Encode)

Trained by Jina AI.

Source: [jinaai/jina-colbert-v2 on HuggingFace](https://huggingface.co/jinaai/jina-colbert-v2)

## Overview

| Field | Value |
|-------|-------|
| Architecture | XLM-RoBERTa |
| Parameters | 559M |
| Tasks | Encode, Score |
| Outputs | Multi-Vec |
| Dimensions | Multi-Vec: 128 |
| Max sequence length | 8,192 tokens |
| License | cc-by-nc-4.0 |
| Inputs | text |
| Languages | multilingual, af, am, ar, as, az, be, bg, bn, br, bs, ca, cs, cy, da, de, el, en, eo, es, et, eu, fa, fi, fr, fy, ga, gd, gl, gu, ha, he, hi, hr, hu, hy, id, is, it, ja, jv, ka, kk, km, kn, ko, ku, ky, la, lo, lt, lv, mg, mk, ml, mn, mr, ms, my, ne, nl, no, om, or, pa, pl, ps, pt, ro, ru, sa, sd, si, sk, sl, so, sq, sr, su, sv, sw, ta, te, th, tl, tr, ug, uk, ur, uz, vi, xh, yi, zh |

## Benchmarks

### CQADupstackPhysicsRetrieval

Domain: scientific · Task: retrieval · Language: en

Duplicate question retrieval from StackExchange Physics

Corpus: 38,314 · Queries: 1,039

**Quality:** ndcg at 10: 0.4047 · map at 10: 0.3496 · mrr at 10: 0.4005

**Performance (L4 b1 c16):** Corpus 24.9K tok/s · Corpus p50 81.3ms · Query 3.0K tok/s · Query p50 55.9ms

[Reference](http://nlp.cis.unimelb.edu.au/resources/cqadupstack/)

### CosQA

Domain: technology · Task: retrieval · Language: en

Code search with natural language queries

Corpus: 6,267 · Queries: 500

**Quality:** ndcg at 10: 0.2607 · map at 10: 0.2037 · mrr at 10: 0.1946

**Performance (L4 b1 c16):** Corpus 13.9K tok/s · Corpus p50 63.3ms · Query 1.5K tok/s · Query p50 59.7ms

[Reference](https://arxiv.org/abs/2105.13239)

### FiQA2018

Domain: finance · Task: retrieval · Language: en

Financial opinion mining and question answering

Corpus: 57,599 · Queries: 648

**Quality:** ndcg at 10: 0.4051 · map at 10: 0.3240 · mrr at 10: 0.4875

**Performance (L4 b1 c16):** Corpus 27.1K tok/s · Corpus p50 93.4ms · Query 3.0K tok/s · Query p50 59.5ms

[Reference](https://sites.google.com/view/fiqa/)

### LegalBenchConsumerContractsQA

Domain: legal · Task: retrieval · Language: en

Question answering on consumer contracts

Corpus: 153 · Queries: 396

**Quality:** ndcg at 10: 0.7615 · map at 10: 0.7107 · mrr at 10: 0.7116

**Performance (L4 b1 c16):** Corpus 30.7K tok/s · Corpus p50 259.5ms · Query 3.4K tok/s · Query p50 60.1ms

[Reference](https://huggingface.co/datasets/nguha/legalbench)

### NFCorpus

Domain: medical · Task: retrieval · Language: en

Biomedical literature search from NutritionFacts.org

Corpus: 3,593 · Queries: 323

**Quality:** ndcg at 10: 0.3583 · map at 10: 0.1422 · mrr at 10: 0.5724

**Performance (L4 b1 c16):** Corpus 33.2K tok/s · Corpus p50 146.1ms · Query 1.5K tok/s · Query p50 55.3ms

[Reference](https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/)

### NanoFiQA2018Retrieval

Domain: finance · Task: retrieval · Language: en

Smaller subset of the FiQA financial QA dataset

**Quality:** ndcg at 10: 0.5208 · map at 10: 0.4318 · mrr at 10: 0.5644

**Performance (L4 b1 c16):** Corpus 28.9K tok/s · Corpus p50 77.4ms · Query 2.6K tok/s · Query p50 49.5ms

[Reference](https://sites.google.com/view/fiqa/)

### SCIDOCS

Domain: scientific · Task: retrieval · Language: en

Citation prediction, document classification, and recommendation for scientific papers

Corpus: 25,656 · Queries: 1,000

**Quality:** ndcg at 10: 0.1779 · map at 10: 0.1045 · mrr at 10: 0.3091

**Performance (L4 b1 c16):** Corpus 28.5K tok/s · Corpus p50 105.7ms · Query 2.9K tok/s · Query p50 57.3ms

[Reference](https://allenai.org/data/scidocs)

### SciFact

Domain: scientific · Task: retrieval · Language: en

Scientific claim verification using research literature

Corpus: 5,183 · Queries: 300

**Quality:** ndcg at 10: 0.6702 · map at 10: 0.6266 · mrr at 10: 0.6391

**Performance (L4 b1 c16):** Corpus 30.9K tok/s · Corpus p50 137.3ms · Query 4.8K tok/s · Query p50 56.4ms

[Reference](https://github.com/allenai/scifact)

### StackOverflowQA

Domain: technology · Task: retrieval · Language: en

Programming question answering from Stack Overflow

Corpus: 19,931 · Queries: 1,994

**Quality:** ndcg at 10: 0.6085 · map at 10: 0.5717 · mrr at 10: 0.5717

**Performance (L4 b1 c16):** Corpus 27.4K tok/s · Corpus p50 127.2ms · Query 58.2K tok/s · Query p50 80.3ms

[Reference](https://arxiv.org/abs/2407.02883)