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lightonai/Reason-ModernColBERT

Open comparison →

Primitive: /score · Score · ModernBERT

Reason-ModernColBERT is a late interaction model trained on the reasonir-hq dataset. It achieves extremely competitive performance on the BRIGHT benchmark aimed at evaluating reasoning-intensive retrieval performance, outperforming all existing models up to 7B (more than 45 times its size) and ev...

Long context

Overview

Hardware: — drives latency, throughput & cost

Size149M params
Tasks /encode · /score
Licensecc-by-nc-4.0
Languagesen
Latency
Throughput
Cost /1M tok

Cost is approximate — computed from list GPU prices; your actual price depends on the provider you deploy SIE with.

Scoring

Inputstext
Max sequence length8,192

Benchmarks

AskUbuntuDupQuestions

technology reranking en

Duplicate question detection from AskUbuntu

Corpus: 6,743 Queries: 360
default
Quality
ndcg at 10 0.6338
map at 10 0.4783
mrr at 10 0.7156
muvera
Quality
ndcg at 10 0.6235
map at 10 0.4634
mrr at 10 0.7084
Reference →

CMedQAv1-reranking

medical reranking zh

Chinese medical question answering reranking (v1)

Corpus: 100,000 Queries: 2,000
default
Quality
ndcg at 10 0.4804
map at 10 0.4118
mrr at 10 0.4980
muvera
Quality
ndcg at 10 0.2331
map at 10 0.1694
mrr at 10 0.2333
Reference →

CMedQAv2-reranking

medical reranking zh

Chinese medical question answering reranking (v2)

Corpus: 108,000 Queries: 4,000
default
Quality
ndcg at 10 0.5024
map at 10 0.4346
mrr at 10 0.5171
muvera
Quality
ndcg at 10 0.2451
map at 10 0.1851
mrr at 10 0.2454
Reference →

CQADupstackPhysicsRetrieval

scientific retrieval en

Duplicate question retrieval from StackExchange Physics

Corpus: 38,314 Queries: 1,039
muvera_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.1321
mrr at 10 0.1620
ndcg at 10 0.1681
default_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.3875
mrr at 10 0.4489
ndcg at 10 0.4442
Reference →

CosQA

technology retrieval en

Code search with natural language queries

Corpus: 6,267 Queries: 500
muvera_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.1637
mrr at 10 0.2028
ndcg at 10 0.2187
default_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.3020
mrr at 10 0.2829
ndcg at 10 0.3896
Reference →

FiQA2018

finance retrieval en

Financial opinion mining and question answering

Corpus: 57,599 Queries: 648
muvera_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.0486
mrr at 10 0.0953
ndcg at 10 0.0701
default_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.3880
mrr at 10 0.5504
ndcg at 10 0.4672
Reference →

LegalBenchConsumerContractsQA

legal retrieval en

Question answering on consumer contracts

Corpus: 153 Queries: 396
muvera_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.4025
mrr at 10 0.4024
ndcg at 10 0.4732
default_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.7882
mrr at 10 0.7895
ndcg at 10 0.8328
Reference →

MMarcoReranking

general reranking zh

Multilingual MARCO passage reranking (Chinese)

default
Quality
ndcg at 10 0.2002
map at 10 0.1512
mrr at 10 0.1536
muvera
Quality
ndcg at 10 0.0714
map at 10 0.0554
mrr at 10 0.0570
Reference →

NFCorpus

medical retrieval en

Biomedical literature search from NutritionFacts.org

Corpus: 3,593 Queries: 323
muvera_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.0596
mrr at 10 0.3258
ndcg at 10 0.1853
default_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.1342
mrr at 10 0.5719
ndcg at 10 0.3582
Reference →

SCIDOCS

scientific retrieval en

Citation prediction, document classification, and recommendation for scientific papers

Corpus: 25,656 Queries: 1,000
muvera_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.0370
mrr at 10 0.1317
ndcg at 10 0.0733
default_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.1200
mrr at 10 0.3406
ndcg at 10 0.2015
Reference →

SciFact

scientific retrieval en

Scientific claim verification using research literature

Corpus: 5,183 Queries: 300
muvera_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.3902
mrr at 10 0.4020
ndcg at 10 0.4383
default_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.7107
mrr at 10 0.7226
ndcg at 10 0.7531
Reference →

StackOverflowQA

technology retrieval en

Programming question answering from Stack Overflow

Corpus: 19,931 Queries: 1,994
muvera_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.1952
mrr at 10 0.1952
ndcg at 10 0.2346
default_candidates-k-50_candidates-model-Alibaba-NLP__gte-multilingual-base
Quality
map at 10 0.6559
mrr at 10 0.6559
ndcg at 10 0.6893
Reference →

Open source inference for agents

Open-source inference for the models behind your agents. Run it yourself, or let us run it for you.

Github 3.3K

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