---
title: colbert-ir/colbertv2.0
description: "[](https://colab.research.google.com/github/stanford-futuredata/ColBERT/blob/main/docs/intro2new.ipynb). BERT, 110M parameters."
canonical_url: https://superlinked.com/models/colbert-ir-colbertv2-0
last_updated: 2026-06-07
---

# colbert-ir/colbertv2.0

[](https://colab.research.google.com/github/stanford-futuredata/ColBERT/blob/main/docs/intro2new.ipynb)

Source: [colbert-ir/colbertv2.0 on HuggingFace](https://huggingface.co/colbert-ir/colbertv2.0)

## Overview

| Field | Value |
|-------|-------|
| Architecture | BERT |
| Parameters | 110M |
| Tasks | Encode, Score |
| Outputs | Multi-Vec |
| Dimensions | Multi-Vec: 128 |
| Max sequence length | 512 tokens |
| License | mit |
| Inputs | text |
| Languages | en |

## Benchmarks

### CQADupstackPhysicsRetrieval

Domain: scientific · Task: retrieval · Language: en

Duplicate question retrieval from StackExchange Physics

Corpus: 38,314 · Queries: 1,039

**Performance (L4 b1 c16):** Corpus 34.0K tok/s · Corpus p50 56.9ms · Query 3.6K tok/s · Query p50 48.5ms

[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

**Performance (L4 b1 c16):** Corpus 16.0K tok/s · Corpus p50 52.1ms · Query 1.9K tok/s · Query p50 50.5ms

[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

**Performance (L4 b1 c16):** Corpus 38.8K tok/s · Corpus p50 60.6ms · Query 3.8K tok/s · Query p50 49.2ms

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

### LegalBenchConsumerContractsQA

Domain: legal · Task: retrieval · Language: en

Question answering on consumer contracts

Corpus: 153 · Queries: 396

**Performance (L4 b1 c16):** Corpus 78.1K tok/s · Corpus p50 94.6ms · Query 5.5K tok/s · Query p50 48.3ms

[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: 0.2647 · map at 10: 0.0913 · mrr at 10: 0.4494

**Performance (L4 b1 c16):** Corpus 52.6K tok/s · Corpus p50 78.8ms · Query 1.5K tok/s · Query p50 51.3ms

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

### NanoFiQA2018Retrieval

Domain: finance · Task: retrieval · Language: en

Smaller subset of the FiQA financial QA dataset

**Variant: default**

**Quality:** ndcg at 10: 0.4675 · map at 10: 0.3893 · mrr at 10: 0.5201

**Performance (L4 b1 c16):** Corpus 43.0K tok/s · Corpus p50 44.7ms · Query 3.9K tok/s · Query p50 34.6ms

**Variant: muvera**

**Quality:** ndcg at 10: 0.4675 · map at 10: 0.3893 · mrr at 10: 0.5201

[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

**Performance (L4 b1 c16):** Corpus 41.4K tok/s · Corpus p50 65.7ms · Query 3.5K tok/s · Query p50 50.5ms

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

### SciFact

Domain: scientific · Task: retrieval · Language: en

Scientific claim verification using research literature

Corpus: 5,183 · Queries: 300

**Performance (L4 b1 c16):** Corpus 53.9K tok/s · Corpus p50 70.6ms · Query 5.4K tok/s · Query p50 48.9ms

[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

**Performance (L4 b1 c16):** Corpus 49.0K tok/s · Corpus p50 69.7ms · Query 64.6K tok/s · Query p50 73.5ms

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