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BAAI/bge-m3

Open comparison →

Primitive: /encode · Encode · XLM-RoBERTa

For more details please refer to our github repo: https://github.com/FlagOpen/FlagEmbedding

Long contextDenseSparseMulti-vector

Overview

Hardware: — drives latency, throughput & cost

Size568M params
Tasks /encode · /score
Licensemit
Latency93 ms
Throughput33.2K tok/s
Cost$0.0067 /1M tok

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

Embedding

Output typesDense · Sparse · Multi-Vec
Dimensionsdense: 1,024 · sparse: 250,002 · multivector: 1,024
Max sequence length8,192
Inputstext

Benchmarks

CQADupstackPhysicsRetrieval

scientific retrieval en

Duplicate question retrieval from StackExchange Physics

Corpus: 38,314 Queries: 1,039
dense
Performance L4 b1 c16
Corpus 27.3K tok/s
Corpus p50 74.8ms
Query 3.1K tok/s
Query p50 45.2ms
multivector
Performance L4 b1 c16
Corpus 28.0K tok/s
Corpus p50 70.7ms
Query 3.2K tok/s
Query p50 44.7ms
sparse
Performance L4 b1 c16
Corpus 27.8K tok/s
Corpus p50 70.8ms
Query 3.3K tok/s
Query p50 44.9ms
Reference →

CosQA

technology retrieval en

Code search with natural language queries

Corpus: 6,267 Queries: 500
dense
Performance L4 b1 c16
Corpus 15.8K tok/s
Corpus p50 51.3ms
Query 1.7K tok/s
Query p50 47.9ms
multivector
Performance L4 b1 c16
Corpus 15.3K tok/s
Corpus p50 51.4ms
Query 1.8K tok/s
Query p50 45.8ms
sparse
Performance L4 b1 c16
Corpus 16.9K tok/s
Corpus p50 51.0ms
Query 1.9K tok/s
Query p50 43.7ms
Reference →

FiQA2018

finance retrieval en

Financial opinion mining and question answering

Corpus: 57,599 Queries: 648
dense
Performance L4 b1 c16
Corpus 28.6K tok/s
Corpus p50 87.3ms
Query 3.1K tok/s
Query p50 48.4ms
multivector
Performance L4 b1 c16
Corpus 33.8K tok/s
Corpus p50 77.8ms
Query 3.6K tok/s
Query p50 44.8ms
sparse
Performance L4 b1 c16
Corpus 30.2K tok/s
Corpus p50 81.3ms
Query 3.3K tok/s
Query p50 46.2ms
Reference →

LegalBenchConsumerContractsQA

legal retrieval en

Question answering on consumer contracts

Corpus: 153 Queries: 396
dense
Performance L4 b1 c16
Corpus 39.5K tok/s
Corpus p50 210.7ms
Query 4.2K tok/s
Query p50 51.7ms
multivector
Performance L4 b1 c16
Corpus 39.1K tok/s
Corpus p50 216.2ms
Query 5.1K tok/s
Query p50 44.0ms
sparse
Performance L4 b1 c16
Corpus 40.6K tok/s
Corpus p50 208.1ms
Query 5.1K tok/s
Query p50 45.0ms
Reference →

NFCorpus

medical retrieval en

Biomedical literature search from NutritionFacts.org

Corpus: 3,593 Queries: 323
default
Quality
ndcg at 10 0.3144
map at 10 0.1174
mrr at 10 0.5243
Performance A10G b1 c4
Corpus 127 tok/s
Corpus p50 9.4s
Query 39 tok/s
Query p50 537.6ms
Performance L4 b1 c16
Corpus 38.1K tok/s
Corpus p50 100.0ms
Query 1.5K tok/s
Query p50 41.0ms
dense
Performance L4 b1 c16
Corpus 34.2K tok/s
Corpus p50 134.0ms
Query 937 tok/s
Query p50 64.2ms
multivector
Performance L4 b1 c16
Corpus 37.9K tok/s
Corpus p50 126.6ms
Query 1.5K tok/s
Query p50 46.1ms
sparse
Performance L4 b1 c16
Corpus 40.0K tok/s
Corpus p50 124.4ms
Query 1.4K tok/s
Query p50 45.0ms
Reference →

NanoFiQA2018Retrieval

finance retrieval en

Smaller subset of the FiQA financial QA dataset

dense
Performance L4 b1 c16
Corpus 28.1K tok/s
Corpus p50 89.9ms
Query 2.5K tok/s
Query p50 59.2ms
default
Quality
ndcg at 10 0.5726
map at 10 0.4957
mrr at 10 0.6467
Performance L4 b1 c16
Corpus 31.2K tok/s
Corpus p50 68.9ms
Query 2.9K tok/s
Query p50 43.3ms
multivector
Performance L4 b1 c16
Corpus 30.6K tok/s
Corpus p50 86.6ms
Query 2.7K tok/s
Query p50 54.1ms
sparse
Performance L4 b1 c16
Corpus 30.3K tok/s
Corpus p50 87.5ms
Query 2.7K tok/s
Query p50 53.3ms
Reference →

SCIDOCS

scientific retrieval en

Citation prediction, document classification, and recommendation for scientific papers

Corpus: 25,656 Queries: 1,000
dense
Performance L4 b1 c16
Corpus 33.2K tok/s
Corpus p50 94.8ms
Query 2.5K tok/s
Query p50 54.2ms
multivector
Performance L4 b1 c16
Corpus 34.4K tok/s
Corpus p50 90.7ms
Query 3.4K tok/s
Query p50 43.0ms
sparse
Performance L4 b1 c16
Corpus 32.5K tok/s
Corpus p50 93.4ms
Query 3.4K tok/s
Query p50 44.7ms
bge_m3_flag
Quality
map at 10 0.0946
mrr at 10 0.2886
ndcg at 10 0.1636
default
Quality
map at 10 0.0946
mrr at 10 0.2886
ndcg at 10 0.1636
Reference →

SciFact

scientific retrieval en

Scientific claim verification using research literature

Corpus: 5,183 Queries: 300
dense
Performance L4 b1 c16
Corpus 37.9K tok/s
Corpus p50 118.2ms
Query 4.2K tok/s
Query p50 48.5ms
multivector
Performance L4 b1 c16
Corpus 38.2K tok/s
Corpus p50 116.5ms
Query 4.9K tok/s
Query p50 44.4ms
sparse
Performance L4 b1 c16
Corpus 37.8K tok/s
Corpus p50 117.6ms
Query 4.2K tok/s
Query p50 47.7ms
bge_m3_flag
Quality
map at 10 0.5942
mrr at 10 0.6102
ndcg at 10 0.6457
default
Quality
map at 10 0.5942
mrr at 10 0.6102
ndcg at 10 0.6457
Reference →

StackOverflowQA

technology retrieval en

Programming question answering from Stack Overflow

Corpus: 19,931 Queries: 1,994
dense
Performance L4 b1 c16
Corpus 33.4K tok/s
Corpus p50 104.7ms
Query 33.8K tok/s
Query p50 138.5ms
multivector
Performance L4 b1 c16
Corpus 33.2K tok/s
Corpus p50 107.6ms
Query 33.8K tok/s
Query p50 137.6ms
sparse
Performance L4 b1 c16
Corpus 32.7K tok/s
Corpus p50 108.4ms
Query 34.8K tok/s
Query p50 137.6ms
bge_m3_flag
Quality
map at 10 0.7798
mrr at 10 0.7798
ndcg at 10 0.8066
default
Quality
map at 10 0.7798
mrr at 10 0.7798
ndcg at 10 0.8066
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 2.1K

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