Gradio

Model Leaderboard Explanation

Welcome to the Model Leaderboard Interface!

Search: Enter keywords for the model name in the search box. Use a semicolon (;) to separate multiple keywords.
Model Type: Choose the model type(s) you're interested in.
Model Size: Select the parameter count range to filter models accordingly.

Click the Filter Data button to update the display with the filtered data.

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
20	jinaai/jina-reranker-v2-base-multilingual	53.44	53.64	5.46	39.67	Unkown	sparse retrieval	38.05

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
6	bm25	53.44	53.64	5.46	39.67	Unkown	sparse retrieval	38.05
20	colbert	40.07	40.35	4.09	29.28	110M	dense retrieval	28.45
19	intfloat/e5-small-v2	35.89	42.17	3.72	33.69	33M	embedding model	28.87
16	facebook/contriever-msmarco	38.31	44.67	3.96	33.69	Unkown	dense retrieval	30.16
17	sentence-transformers/gtr-t5-base	37.65	43.96	3.9	34.52	110M	dense retrieval	30.01
14	sentence-transformers/gtr-t5-large	42.25	48.61	4.36	37.07	335M	dense retrieval	33.07
11	sentence-transformers/all-MiniLM-L6-v2	48.27	48.58	3.77	36.08	22M	embedding model	34.17
18	intfloat/e5-base-v2	37.19	43.51	3.88	31.87	109M	embedding model	29.11
15	intfloat/e5-large-v2	40.34	46.64	4.17	36.56	335M	embedding model	31.93
8	Alibaba-NLP/gte-base-en-v1.5	45.9	52.31	4.75	40.52	137M	embedding model	35.87
7	BAAI/bge-base-en-v1.5	52.91	53.14	4.23	41.45	109M	embedding model	37.93
4	BAAI/bge-large-en-v1.5	58.16	58.39	4.76	45.91	335M	embedding model	41.81
5	intfloat/e5-mistral-7b-instruct	50.72	57.11	5.24	43.33	7B	embedding model	39.1
10	Alibaba-NLP/gte-large-en-v1.5	43.74	50.14	4.54	38.76	434M	embedding model	34.3
3	bzantium/NV-Embed-v1	55.26	60.83	5.85	46.35	7.85B	embedding model	42.07
9	castorini/monot5-base-msmarco	51.29	51.6	4.07	36.46	Unkown	re-ranking model	35.86
2	jinaai/jina-reranker-v2-base-multilingual	57.68	64.11	5.96	51.18	278M	re-ranking model	44.73
12	BAAI/bge-reranker-v2-gemma	42.97	49.35	4.45	38.28	2.51B	re-ranking model	33.76
1	BAAI/bge-reranker-v2-m3	58.83	65.29	6.06	51.15	568M	re-ranking model	45.33
13	mixedbread-ai/mxbai-rerank-large-v1	46.42	47.94	5.14	33.4	435M	re-ranking model	33.23

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
19	jinaai/jina-reranker-v2-base-multilingual	14.47	36.63	10.32	28.74	Unkown	sparse retrieval	23.93

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
8	bm25	23.4	36.63	6.94	28.74	Unkown	sparse retrieval	23.93
19	colbert	14.47	20.05	2.98	16.18	110M	dense retrieval	13.42
10	intfloat/e5-small-v2	20.75	33.67	6.38	26.54	33M	embedding model	21.83
15	facebook/contriever-msmarco	18.69	28.82	5.31	23.04	Unkown	dense retrieval	18.96
17	sentence-transformers/gtr-t5-base	18.95	27.54	4.78	20.85	110M	dense retrieval	18.03
14	sentence-transformers/gtr-t5-large	20.55	30.66	5.39	24.4	335M	dense retrieval	20.25
20	sentence-transformers/all-MiniLM-L6-v2	12.98	18.88	3.27	12.71	22M	embedding model	11.96
11	intfloat/e5-base-v2	21.14	32.9	6	24.59	109M	embedding model	21.16
13	intfloat/e5-large-v2	20.58	31.5	5.8	23.51	335M	embedding model	20.35
7	Alibaba-NLP/gte-base-en-v1.5	23.72	37.09	6.86	29.06	137M	embedding model	24.19
9	BAAI/bge-base-en-v1.5	23.47	35.28	6.43	26.48	109M	embedding model	22.92
6	BAAI/bge-large-en-v1.5	24.94	39.14	7.34	30.29	335M	embedding model	25.43
4	intfloat/e5-mistral-7b-instruct	25.69	39.18	7.53	29.95	7B	embedding model	25.59
12	Alibaba-NLP/gte-large-en-v1.5	19.76	31.61	5.84	24.51	434M	embedding model	20.43
5	bzantium/NV-Embed-v1	24.9	38.8	7.69	30.6	7.85B	embedding model	25.5
16	castorini/monot5-base-msmarco	17.05	29.39	5.94	22.69	Unkown	re-ranking model	18.77
1	jinaai/jina-reranker-v2-base-multilingual	32.39	49.67	10.32	41.34	278M	re-ranking model	33.43
3	BAAI/bge-reranker-v2-gemma	27.05	42.06	8.75	33.86	2.51B	re-ranking model	27.93
2	BAAI/bge-reranker-v2-m3	30.75	44.46	8.72	35.2	568M	re-ranking model	29.78
18	mixedbread-ai/mxbai-rerank-large-v1	18.18	26.02	4.06	17.81	435M	re-ranking model	16.52

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
13	jinaai/jina-reranker-v2-base-multilingual	36.62	45.76	10.11	39.71	Unkown	sparse retrieval	32.48

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
13	bm25	36.62	45.76	7.83	39.71	Unkown	sparse retrieval	32.48
19	colbert	26.59	31.87	4.7	24.96	110M	dense retrieval	22.03
16	intfloat/e5-small-v2	33.68	43.4	7.03	36.58	33M	embedding model	30.17
20	facebook/contriever-msmarco	22.63	26.91	3.78	21.32	Unkown	dense retrieval	18.66
9	sentence-transformers/gtr-t5-base	39.45	48.63	7.69	42.62	110M	dense retrieval	34.6
7	sentence-transformers/gtr-t5-large	40.73	51.56	8.58	42.59	335M	dense retrieval	35.86
17	sentence-transformers/all-MiniLM-L6-v2	34.05	45.07	7.3	33.37	22M	embedding model	29.95
12	intfloat/e5-base-v2	38.29	48.8	7.8	39.32	109M	embedding model	33.55
5	intfloat/e5-large-v2	41.95	53.01	8.62	44.9	335M	embedding model	37.12
14	Alibaba-NLP/gte-base-en-v1.5	37.59	45.86	6.91	37.98	137M	embedding model	32.08
3	BAAI/bge-base-en-v1.5	43.35	54.59	8.98	44.37	109M	embedding model	37.82
6	BAAI/bge-large-en-v1.5	42.62	52.5	8.51	44.31	335M	embedding model	36.98
10	intfloat/e5-mistral-7b-instruct	37.78	49.14	7.93	42.08	7B	embedding model	34.23
15	Alibaba-NLP/gte-large-en-v1.5	35.7	47.48	7.77	36.57	434M	embedding model	31.88
1	bzantium/NV-Embed-v1	44.76	58.32	10.11	49.45	7.85B	embedding model	40.66
11	castorini/monot5-base-msmarco	41.03	48.67	6.93	38.11	Unkown	re-ranking model	33.69
2	jinaai/jina-reranker-v2-base-multilingual	44.53	56.94	10.25	44.67	278M	re-ranking model	39.1
8	BAAI/bge-reranker-v2-gemma	39.69	51.53	9.19	41.26	2.51B	re-ranking model	35.42
4	BAAI/bge-reranker-v2-m3	40.63	54.85	9.75	43.4	568M	re-ranking model	37.16
18	mixedbread-ai/mxbai-rerank-large-v1	29.04	37.83	6.72	27.97	435M	re-ranking model	25.39

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
20	jinaai/jina-reranker-v2-base-multilingual	37.82	45.34	6.74	36.04	Unkown	sparse retrieval	31.49

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
8	bm25	37.82	45.34	6.74	36.04	Unkown	sparse retrieval	31.49
20	colbert	27.04	30.75	3.93	23.47	110M	dense retrieval	21.3
16	intfloat/e5-small-v2	30.11	39.74	5.71	32.27	33M	embedding model	26.96
19	facebook/contriever-msmarco	26.54	33.46	4.35	26.02	Unkown	dense retrieval	22.59
15	sentence-transformers/gtr-t5-base	32.02	40.04	5.46	32.66	110M	dense retrieval	27.55
11	sentence-transformers/gtr-t5-large	34.51	43.61	6.11	34.68	335M	dense retrieval	29.73
17	sentence-transformers/all-MiniLM-L6-v2	31.77	37.51	4.78	27.38	22M	embedding model	25.36
14	intfloat/e5-base-v2	32.21	41.73	5.89	31.93	109M	embedding model	27.94
10	intfloat/e5-large-v2	34.29	43.72	6.2	34.99	335M	embedding model	29.8
9	Alibaba-NLP/gte-base-en-v1.5	35.74	45.09	6.17	35.86	137M	embedding model	30.71
6	BAAI/bge-base-en-v1.5	39.91	47.67	6.54	37.44	109M	embedding model	32.89
4	BAAI/bge-large-en-v1.5	41.91	50.01	6.87	40.17	335M	embedding model	34.74
5	intfloat/e5-mistral-7b-instruct	38.06	48.48	6.9	38.46	7B	embedding model	32.97
13	Alibaba-NLP/gte-large-en-v1.5	33.07	43.08	6.05	33.28	434M	embedding model	28.87
3	bzantium/NV-Embed-v1	41.64	52.65	7.88	42.13	7.85B	embedding model	36.08
12	castorini/monot5-base-msmarco	36.46	43.22	5.65	32.42	Unkown	re-ranking model	29.44
1	jinaai/jina-reranker-v2-base-multilingual	44.87	56.91	8.84	45.73	278M	re-ranking model	39.09
7	BAAI/bge-reranker-v2-gemma	36.57	47.65	7.46	37.8	2.51B	re-ranking model	32.37
2	BAAI/bge-reranker-v2-m3	43.41	54.87	8.18	43.25	568M	re-ranking model	37.43
18	mixedbread-ai/mxbai-rerank-large-v1	31.21	37.26	5.31	26.39	435M	re-ranking model	25.04

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
15	jinaai/jina-reranker-v2-base-multilingual	25.24	25.63	2.78	19.44	Unkown	sparse retrieval	18.27

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
7	bm25	25.24	25.63	2.78	19.44	Unkown	sparse retrieval	18.27
15	colbert	20	20.26	2.19	14.44	110M	dense retrieval	14.22
17	intfloat/e5-small-v2	16.68	17.13	1.91	13	33M	embedding model	12.18
18	facebook/contriever-msmarco	16.54	17.05	1.89	12.19	Unkown	dense retrieval	11.92
16	sentence-transformers/gtr-t5-base	18.18	18.5	2.03	13.66	110M	dense retrieval	13.09
10	sentence-transformers/gtr-t5-large	21.07	21.42	2.35	16.05	335M	dense retrieval	15.22
20	sentence-transformers/all-MiniLM-L6-v2	15.63	16.06	1.82	11.25	22M	embedding model	11.19
19	intfloat/e5-base-v2	16.14	16.56	1.88	11.98	109M	embedding model	11.64
14	intfloat/e5-large-v2	19.76	20.13	2.22	15.55	335M	embedding model	14.41
11	Alibaba-NLP/gte-base-en-v1.5	20.76	21.18	2.33	15.4	137M	embedding model	14.92
12	BAAI/bge-base-en-v1.5	20.62	21.12	2.34	15.28	109M	embedding model	14.84
8	BAAI/bge-large-en-v1.5	22.86	23.27	2.55	16.6	335M	embedding model	16.32
9	intfloat/e5-mistral-7b-instruct	21.89	22.37	2.47	14.89	7B	embedding model	15.41
13	Alibaba-NLP/gte-large-en-v1.5	20.98	21.37	2.35	14.55	434M	embedding model	14.81
1	bzantium/NV-Embed-v1	35.43	39.14	3.87	35.37	7.85B	embedding model	28.45
6	castorini/monot5-base-msmarco	26.67	27.3	2.96	19.2	Unkown	re-ranking model	19.03
5	jinaai/jina-reranker-v2-base-multilingual	29.98	30.38	3.27	22.82	278M	re-ranking model	21.61
2	BAAI/bge-reranker-v2-gemma	34.42	34.94	3.75	27.04	2.51B	re-ranking model	25.04
4	BAAI/bge-reranker-v2-m3	30.12	30.69	3.29	22.42	568M	re-ranking model	21.63
3	mixedbread-ai/mxbai-rerank-large-v1	30.74	31.39	3.3	21.88	435M	re-ranking model	21.83

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
15	jinaai/jina-reranker-v2-base-multilingual	14.99	25.83	10.02	21.55	Unkown	sparse retrieval	16.59

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
15	bm25	14.99	25.83	5.34	20.2	Unkown	sparse retrieval	16.59
13	colbert	14.95	26.37	5.3	21.55	110M	dense retrieval	17.04
17	intfloat/e5-small-v2	14.87	25	5.13	19.24	33M	embedding model	16.06
16	facebook/contriever-msmarco	13.58	25.56	5.81	20.2	Unkown	dense retrieval	16.29
19	sentence-transformers/gtr-t5-base	14.93	22.95	4.36	16.75	110M	dense retrieval	14.75
12	sentence-transformers/gtr-t5-large	17.48	27.57	5.36	21.28	335M	dense retrieval	17.92
20	sentence-transformers/all-MiniLM-L6-v2	9.86	15.58	3.04	11.04	22M	embedding model	9.88
14	intfloat/e5-base-v2	14.69	26.15	5.48	20.06	109M	embedding model	16.59
18	intfloat/e5-large-v2	15.13	24.97	5.09	18.42	335M	embedding model	15.9
11	Alibaba-NLP/gte-base-en-v1.5	17.03	29.16	6.03	21.58	137M	embedding model	18.45
9	BAAI/bge-base-en-v1.5	17.2	29.55	6.16	22.13	109M	embedding model	18.76
8	BAAI/bge-large-en-v1.5	17.41	30.25	6.44	22.59	335M	embedding model	19.17
6	intfloat/e5-mistral-7b-instruct	19.47	33.34	7.45	25.81	7B	embedding model	21.52
10	Alibaba-NLP/gte-large-en-v1.5	16.89	29.08	6.32	22.21	434M	embedding model	18.63
4	bzantium/NV-Embed-v1	22.08	37.36	8.44	30.43	7.85B	embedding model	24.58
5	castorini/monot5-base-msmarco	18.35	34.4	7.78	27.63	Unkown	re-ranking model	22.04
2	jinaai/jina-reranker-v2-base-multilingual	25.39	42.75	9.43	33.85	278M	re-ranking model	27.86
1	BAAI/bge-reranker-v2-gemma	27.03	45.37	10.02	36.68	2.51B	re-ranking model	29.77
3	BAAI/bge-reranker-v2-m3	24.15	40.87	9.09	32.47	568M	re-ranking model	26.64
7	mixedbread-ai/mxbai-rerank-large-v1	18.29	30.44	5.76	23.64	435M	re-ranking model	19.53

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
12	jinaai/jina-reranker-v2-base-multilingual	23.22	30.48	5.45	25.66	Unkown	sparse retrieval	17.11

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
12	bm25	23.22	30.48	5.45	25.66	Unkown	sparse retrieval	21.2
19	colbert	20.2	25.14	3.81	19.29	110M	dense retrieval	17.11
13	intfloat/e5-small-v2	21.48	30.46	5.64	25.36	33M	embedding model	20.73
20	facebook/contriever-msmarco	18.06	22.56	3.28	18.23	Unkown	dense retrieval	15.54
14	sentence-transformers/gtr-t5-base	22.41	29.32	5.12	23.78	110M	dense retrieval	20.16
10	sentence-transformers/gtr-t5-large	24.62	31.82	5.7	25.92	335M	dense retrieval	22.02
16	sentence-transformers/all-MiniLM-L6-v2	21.05	29.69	5.25	23.25	22M	embedding model	19.81
17	intfloat/e5-base-v2	21.16	28.02	4.99	22.48	109M	embedding model	19.16
9	intfloat/e5-large-v2	24.39	33.36	6.27	27.49	335M	embedding model	22.88
15	Alibaba-NLP/gte-base-en-v1.5	23.44	29.82	4.92	22.37	137M	embedding model	20.14
8	BAAI/bge-base-en-v1.5	25.29	33.41	5.88	27.29	109M	embedding model	22.97
11	BAAI/bge-large-en-v1.5	24.78	31.91	5.57	25.63	335M	embedding model	21.97
5	intfloat/e5-mistral-7b-instruct	29.87	39.26	6.84	31.86	7B	embedding model	26.96
18	Alibaba-NLP/gte-large-en-v1.5	19.57	28.52	5.38	22.35	434M	embedding model	18.95
3	bzantium/NV-Embed-v1	34.89	46.24	8.27	40.68	7.85B	embedding model	32.52
2	castorini/monot5-base-msmarco	37.88	47.12	7.89	37.29	Unkown	re-ranking model	32.55
4	jinaai/jina-reranker-v2-base-multilingual	36.13	46.54	8.19	38.8	278M	re-ranking model	32.41
1	BAAI/bge-reranker-v2-gemma	39.07	50.49	9.27	40.93	2.51B	re-ranking model	34.94
6	BAAI/bge-reranker-v2-m3	26.86	36.25	7.06	30.98	568M	re-ranking model	25.29
7	mixedbread-ai/mxbai-rerank-large-v1	26.94	35.07	5.89	27.45	435M	re-ranking model	23.84

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
10	jinaai/jina-reranker-v2-base-multilingual	21.15	27.31	4.53	21.77	Unkown	sparse retrieval	18.69

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
10	bm25	21.15	27.31	4.53	21.77	Unkown	sparse retrieval	18.69
16	colbert	18.38	23.93	3.77	18.43	110M	dense retrieval	16.13
15	intfloat/e5-small-v2	17.68	24.2	4.23	19.2	33M	embedding model	16.32
19	facebook/contriever-msmarco	16.06	21.72	3.66	16.88	Unkown	dense retrieval	14.58
17	sentence-transformers/gtr-t5-base	18.51	23.59	3.83	18.07	110M	dense retrieval	16
11	sentence-transformers/gtr-t5-large	21.06	26.93	4.47	21.08	335M	dense retrieval	18.39
20	sentence-transformers/all-MiniLM-L6-v2	15.51	20.44	3.37	15.18	22M	embedding model	13.63
18	intfloat/e5-base-v2	17.33	23.58	4.12	18.17	109M	embedding model	15.8
13	intfloat/e5-large-v2	19.76	26.15	4.53	20.48	335M	embedding model	17.73
12	Alibaba-NLP/gte-base-en-v1.5	20.41	26.72	4.43	19.78	137M	embedding model	17.83
9	BAAI/bge-base-en-v1.5	21.04	28.03	4.79	21.56	109M	embedding model	18.85
8	BAAI/bge-large-en-v1.5	21.69	28.48	4.85	21.61	335M	embedding model	19.16
7	intfloat/e5-mistral-7b-instruct	23.74	31.66	5.59	24.19	7B	embedding model	21.29
14	Alibaba-NLP/gte-large-en-v1.5	19.14	26.32	4.68	19.71	434M	embedding model	17.46
2	bzantium/NV-Embed-v1	30.8	40.91	6.86	35.5	7.85B	embedding model	28.52
4	castorini/monot5-base-msmarco	27.63	36.27	6.21	28.04	Unkown	re-ranking model	24.54
3	jinaai/jina-reranker-v2-base-multilingual	30.5	39.89	6.97	31.82	278M	re-ranking model	27.29
1	BAAI/bge-reranker-v2-gemma	33.51	43.6	7.68	34.88	2.51B	re-ranking model	29.92
5	BAAI/bge-reranker-v2-m3	27.04	35.94	6.48	28.62	568M	re-ranking model	24.52
6	mixedbread-ai/mxbai-rerank-large-v1	25.32	32.3	4.98	24.32	435M	re-ranking model	21.73

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
17	jinaai/jina-reranker-v2-base-multilingual	42.54	52.46	4.76	38.44	Unkown	sparse retrieval	35.44

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
8	bm25	46.1	52.46	4.76	38.44	Unkown	sparse retrieval	35.44
17	colbert	42.54	42.79	4.35	31.73	110M	dense retrieval	30.35
11	intfloat/e5-small-v2	46.17	47.53	5.39	35.89	33M	embedding model	33.75
13	facebook/contriever-msmarco	45.49	46.61	5.09	34.21	Unkown	dense retrieval	32.85
14	sentence-transformers/gtr-t5-base	41.76	48.15	4.32	36.27	110M	dense retrieval	32.62
6	sentence-transformers/gtr-t5-large	56.28	56.5	4.55	42.02	335M	dense retrieval	39.84
7	sentence-transformers/all-MiniLM-L6-v2	55.21	55.46	4.45	38.66	22M	embedding model	38.45
20	intfloat/e5-base-v2	33.36	39.65	3.5	27.71	109M	embedding model	26.05
19	intfloat/e5-large-v2	33.91	40.25	3.54	29.65	335M	embedding model	26.84
15	Alibaba-NLP/gte-base-en-v1.5	41.64	48.04	4.33	35.54	137M	embedding model	32.39
5	BAAI/bge-base-en-v1.5	56.53	56.73	4.59	41.84	109M	embedding model	39.92
3	BAAI/bge-large-en-v1.5	59.18	59.41	4.86	46.11	335M	embedding model	42.39
9	intfloat/e5-mistral-7b-instruct	44.36	50.8	4.61	38.03	7B	embedding model	34.45
10	Alibaba-NLP/gte-large-en-v1.5	44.31	50.71	4.58	37.31	434M	embedding model	34.23
2	bzantium/NV-Embed-v1	61.61	61.95	5.13	47.65	7.85B	embedding model	44.09
16	castorini/monot5-base-msmarco	43.96	44.34	3.36	33.13	Unkown	re-ranking model	31.2
4	jinaai/jina-reranker-v2-base-multilingual	50.74	57.12	5.29	46.71	278M	re-ranking model	39.96
18	BAAI/bge-reranker-v2-gemma	38	44.44	3.97	34.75	2.51B	re-ranking model	30.29
1	BAAI/bge-reranker-v2-m3	63.71	64.01	5.36	48.93	568M	re-ranking model	45.5
12	mixedbread-ai/mxbai-rerank-large-v1	43.38	49.77	4.44	36.08	435M	re-ranking model	33.42

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
12	jinaai/jina-reranker-v2-base-multilingual	17.47	29.98	5.99	23.72	Unkown	sparse retrieval	19.29

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
12	bm25	17.47	29.98	5.99	23.72	Unkown	sparse retrieval	19.29
20	colbert	12.7	18.26	2.81	14.35	110M	dense retrieval	12.03
14	intfloat/e5-small-v2	17.46	28.04	5.14	21.34	33M	embedding model	17.99
19	facebook/contriever-msmarco	13.75	22.69	4.16	17.11	Unkown	dense retrieval	14.43
17	sentence-transformers/gtr-t5-base	17.91	26.88	4.54	20.66	110M	dense retrieval	17.5
10	sentence-transformers/gtr-t5-large	19.93	30.69	5.44	23.7	335M	dense retrieval	19.94
16	sentence-transformers/all-MiniLM-L6-v2	17.74	27.5	4.78	20.53	22M	embedding model	17.64
9	intfloat/e5-base-v2	21.28	32.91	6.11	24.4	109M	embedding model	21.18
11	intfloat/e5-large-v2	19.74	29.93	5.53	22.84	335M	embedding model	19.51
5	Alibaba-NLP/gte-base-en-v1.5	23.67	35.83	6.41	26.96	137M	embedding model	23.22
7	BAAI/bge-base-en-v1.5	21.74	32.94	5.79	25.83	109M	embedding model	21.57
8	BAAI/bge-large-en-v1.5	22.26	32.71	5.48	25.39	335M	embedding model	21.46
6	intfloat/e5-mistral-7b-instruct	21.41	35.25	6.75	26.86	7B	embedding model	22.57
13	Alibaba-NLP/gte-large-en-v1.5	18.04	28.99	5.24	21.47	434M	embedding model	18.43
2	bzantium/NV-Embed-v1	24.62	38.69	7.32	29.37	7.85B	embedding model	25
15	castorini/monot5-base-msmarco	17.14	28.15	5.41	20.97	Unkown	re-ranking model	17.92
1	jinaai/jina-reranker-v2-base-multilingual	28.06	42.97	8.38	33.63	278M	re-ranking model	28.26
3	BAAI/bge-reranker-v2-gemma	23.84	38.16	7.9	29.76	2.51B	re-ranking model	24.92
4	BAAI/bge-reranker-v2-m3	25.54	38.07	6.86	27.82	568M	re-ranking model	24.57
18	mixedbread-ai/mxbai-rerank-large-v1	17.82	24.79	3.7	17.18	435M	re-ranking model	15.87

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
12	jinaai/jina-reranker-v2-base-multilingual	31.18	42.21	7.24	22.25	Unkown	sparse retrieval	28.98

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
12	bm25	31.18	42.21	7.24	35.3	Unkown	sparse retrieval	28.98
19	colbert	22.93	28.06	3.9	22.25	110M	dense retrieval	19.29
14	intfloat/e5-small-v2	30.44	39.98	6.25	32.05	33M	embedding model	27.18
20	facebook/contriever-msmarco	21.35	26.6	3.64	18.62	Unkown	dense retrieval	17.55
13	sentence-transformers/gtr-t5-base	32.04	41.17	6.22	34.58	110M	dense retrieval	28.5
15	sentence-transformers/gtr-t5-large	30.82	40.04	6.22	31.07	335M	dense retrieval	27.04
17	sentence-transformers/all-MiniLM-L6-v2	28.73	36.67	5.49	26.93	22M	embedding model	24.46
7	intfloat/e5-base-v2	35.47	47.33	7.78	39.09	109M	embedding model	32.42
11	intfloat/e5-large-v2	34.15	44.3	7.05	35.53	335M	embedding model	30.26
8	Alibaba-NLP/gte-base-en-v1.5	35.44	47.28	7.5	39.2	137M	embedding model	32.35
3	BAAI/bge-base-en-v1.5	38.85	50.16	7.96	39.76	109M	embedding model	34.18
5	BAAI/bge-large-en-v1.5	36.88	47.57	7.58	40.01	335M	embedding model	33.01
10	intfloat/e5-mistral-7b-instruct	35.39	44.84	7.08	36.44	7B	embedding model	30.94
9	Alibaba-NLP/gte-large-en-v1.5	35.78	47.1	7.83	38.23	434M	embedding model	32.24
1	bzantium/NV-Embed-v1	41.42	54.92	9.13	45.19	7.85B	embedding model	37.67
16	castorini/monot5-base-msmarco	30.5	39.38	5.68	30.41	Unkown	re-ranking model	26.5
6	jinaai/jina-reranker-v2-base-multilingual	35.91	49.02	8.56	38.07	278M	re-ranking model	32.89
4	BAAI/bge-reranker-v2-gemma	38.29	49	8.71	37.96	2.51B	re-ranking model	33.49
2	BAAI/bge-reranker-v2-m3	39.53	54.39	9.57	42	568M	re-ranking model	36.37
18	mixedbread-ai/mxbai-rerank-large-v1	25.66	33.92	6.22	23.68	435M	re-ranking model	22.37

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
11	jinaai/jina-reranker-v2-base-multilingual	31.58	41.55	3.69	32.49	Unkown	sparse retrieval	20.56

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
11	bm25	31.58	41.55	6	32.49	Unkown	sparse retrieval	27.9
20	colbert	26.06	29.71	3.69	22.78	110M	dense retrieval	20.56
14	intfloat/e5-small-v2	31.36	38.51	5.6	29.76	33M	embedding model	26.31
19	facebook/contriever-msmarco	26.86	31.97	4.3	23.32	Unkown	dense retrieval	21.61
15	sentence-transformers/gtr-t5-base	30.57	38.74	5.03	30.5	110M	dense retrieval	26.21
9	sentence-transformers/gtr-t5-large	35.68	42.41	5.4	32.27	335M	dense retrieval	28.94
12	sentence-transformers/all-MiniLM-L6-v2	33.9	39.88	4.91	28.71	22M	embedding model	26.85
13	intfloat/e5-base-v2	30.04	39.96	5.79	30.4	109M	embedding model	26.55
16	intfloat/e5-large-v2	29.27	38.16	5.38	29.34	335M	embedding model	25.54
7	Alibaba-NLP/gte-base-en-v1.5	33.58	43.72	6.08	33.9	137M	embedding model	29.32
5	BAAI/bge-base-en-v1.5	39.04	46.61	6.11	35.81	109M	embedding model	31.89
4	BAAI/bge-large-en-v1.5	39.44	46.56	5.97	37.17	335M	embedding model	32.29
8	intfloat/e5-mistral-7b-instruct	33.72	43.63	6.14	33.78	7B	embedding model	29.32
10	Alibaba-NLP/gte-large-en-v1.5	32.71	42.27	5.89	32.34	434M	embedding model	28.3
1	bzantium/NV-Embed-v1	42.55	51.85	7.2	40.74	7.85B	embedding model	35.58
17	castorini/monot5-base-msmarco	30.54	37.29	4.82	28.17	Unkown	re-ranking model	25.2
3	jinaai/jina-reranker-v2-base-multilingual	38.24	49.7	7.41	39.47	278M	re-ranking model	33.7
6	BAAI/bge-reranker-v2-gemma	33.38	43.87	6.86	34.15	2.51B	re-ranking model	29.56
2	BAAI/bge-reranker-v2-m3	42.92	52.16	7.26	39.58	568M	re-ranking model	35.48
18	mixedbread-ai/mxbai-rerank-large-v1	28.96	36.16	4.79	25.65	435M	re-ranking model	23.89

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
15	jinaai/jina-reranker-v2-base-multilingual	19.27	19.69	2.18	14.92	Unkown	sparse retrieval	14.02

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
15	bm25	19.27	19.69	2.18	14.92	Unkown	sparse retrieval	14.02
13	colbert	20.78	21.12	2.27	15.23	110M	dense retrieval	14.85
11	intfloat/e5-small-v2	21.6	22.02	2.42	15.96	33M	embedding model	15.5
18	facebook/contriever-msmarco	18.69	19.11	2.02	13.74	Unkown	dense retrieval	13.39
14	sentence-transformers/gtr-t5-base	20.43	20.96	2.3	15.34	110M	dense retrieval	14.76
7	sentence-transformers/gtr-t5-large	24.83	25.26	2.74	18.3	335M	dense retrieval	17.78
12	sentence-transformers/all-MiniLM-L6-v2	21.21	21.62	2.38	14.51	22M	embedding model	14.93
19	intfloat/e5-base-v2	16.76	17.22	1.94	11.91	109M	embedding model	11.96
17	intfloat/e5-large-v2	18.91	19.32	2.15	14.39	335M	embedding model	13.69
20	Alibaba-NLP/gte-base-en-v1.5	15.5	15.98	1.82	10.37	137M	embedding model	10.92
10	BAAI/bge-base-en-v1.5	21.81	22.28	2.46	15.73	109M	embedding model	15.57
8	BAAI/bge-large-en-v1.5	22.7	23.23	2.56	16.29	335M	embedding model	16.19
16	intfloat/e5-mistral-7b-instruct	19.77	20.14	2.24	13.77	7B	embedding model	13.98
6	Alibaba-NLP/gte-large-en-v1.5	26.45	26.68	2.07	26.14	434M	embedding model	20.33
2	bzantium/NV-Embed-v1	33.01	36.7	3.63	33.97	7.85B	embedding model	26.82
9	castorini/monot5-base-msmarco	21.92	22.76	2.51	16.63	Unkown	re-ranking model	15.95
3	jinaai/jina-reranker-v2-base-multilingual	29.1	32.78	3.23	31.61	278M	re-ranking model	24.18
1	BAAI/bge-reranker-v2-gemma	36.42	40.23	3.98	31.46	2.51B	re-ranking model	28.02
4	BAAI/bge-reranker-v2-m3	30.66	31.37	3.36	22.72	568M	re-ranking model	22.03
5	mixedbread-ai/mxbai-rerank-large-v1	29.15	29.8	3.13	21.07	435M	re-ranking model	20.79

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
16	jinaai/jina-reranker-v2-base-multilingual	12.03	20.38	4.71	16.92	Unkown	sparse retrieval	13.92

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
16	bm25	12.03	22	4.71	16.92	Unkown	sparse retrieval	13.92
17	colbert	11.16	20.38	3.9	15.49	110M	dense retrieval	12.73
15	intfloat/e5-small-v2	12.73	22.71	4.58	17.17	33M	embedding model	14.3
19	facebook/contriever-msmarco	10.54	19.54	4.13	14.45	Unkown	dense retrieval	12.17
20	sentence-transformers/gtr-t5-base	11.52	19.28	3.62	14.25	110M	dense retrieval	12.16
13	sentence-transformers/gtr-t5-large	14.28	23.97	4.63	17.83	335M	dense retrieval	15.18
18	sentence-transformers/all-MiniLM-L6-v2	11.53	20.14	3.95	15.04	22M	embedding model	12.66
8	intfloat/e5-base-v2	15.27	26.68	5.48	20.07	109M	embedding model	16.88
9	intfloat/e5-large-v2	15.35	25.41	5.11	18.9	335M	embedding model	16.19
11	Alibaba-NLP/gte-base-en-v1.5	15.39	25.56	4.99	18.48	137M	embedding model	16.11
7	BAAI/bge-base-en-v1.5	15.21	27.52	5.6	20.57	109M	embedding model	17.22
12	BAAI/bge-large-en-v1.5	14.2	24.78	4.88	19.66	335M	embedding model	15.88
10	intfloat/e5-mistral-7b-instruct	15.21	25.11	5.12	19.12	7B	embedding model	16.14
14	Alibaba-NLP/gte-large-en-v1.5	13.86	22.76	4.48	16.33	434M	embedding model	14.36
4	bzantium/NV-Embed-v1	19.57	32.75	6.67	25.14	7.85B	embedding model	21.03
5	castorini/monot5-base-msmarco	16.2	29.55	6.34	23.55	Unkown	re-ranking model	18.91
2	jinaai/jina-reranker-v2-base-multilingual	20.7	34.27	7.06	26.35	278M	re-ranking model	22.09
1	BAAI/bge-reranker-v2-gemma	22.13	37.1	7.79	29.41	2.51B	re-ranking model	24.1
3	BAAI/bge-reranker-v2-m3	19.7	33.96	7.16	26.01	568M	re-ranking model	21.71
6	mixedbread-ai/mxbai-rerank-large-v1	17.52	27.93	4.97	20.26	435M	re-ranking model	17.67

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
15	jinaai/jina-reranker-v2-base-multilingual	19.51	27.09	4.93	22.85	Unkown	sparse retrieval	11.14

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
15	bm25	19.51	27.09	4.93	22.85	Unkown	sparse retrieval	18.6
20	colbert	12.44	16.47	2.69	12.96	110M	dense retrieval	11.14
12	intfloat/e5-small-v2	21.47	29.84	5.51	23.91	33M	embedding model	20.18
19	facebook/contriever-msmarco	13.72	17.71	2.72	13.22	Unkown	dense retrieval	11.84
18	sentence-transformers/gtr-t5-base	14.41	20.32	3.56	15.96	110M	dense retrieval	13.56
16	sentence-transformers/gtr-t5-large	20.05	27.18	4.83	19.6	335M	dense retrieval	17.92
17	sentence-transformers/all-MiniLM-L6-v2	16.59	24.38	4.3	18.67	22M	embedding model	15.99
13	intfloat/e5-base-v2	20.7	29.25	5.44	23.8	109M	embedding model	19.8
8	intfloat/e5-large-v2	22.9	30.52	5.54	25.72	335M	embedding model	21.17
6	Alibaba-NLP/gte-base-en-v1.5	24.22	31.99	5.46	25.04	137M	embedding model	21.68
14	BAAI/bge-base-en-v1.5	20.52	27.53	4.82	22.33	109M	embedding model	18.8
9	BAAI/bge-large-en-v1.5	23.29	30.99	5.36	24.49	335M	embedding model	21.03
10	intfloat/e5-mistral-7b-instruct	23.57	30.57	4.94	22.86	7B	embedding model	20.48
7	Alibaba-NLP/gte-large-en-v1.5	22.95	31.94	5.81	25.86	434M	embedding model	21.64
3	bzantium/NV-Embed-v1	31.52	42.06	7.43	33.9	7.85B	embedding model	28.73
4	castorini/monot5-base-msmarco	32.87	41.58	6.73	33.22	Unkown	re-ranking model	28.6
2	jinaai/jina-reranker-v2-base-multilingual	34.06	44.45	7.58	36.35	278M	re-ranking model	30.61
1	BAAI/bge-reranker-v2-gemma	35.65	46.74	8.36	37.14	2.51B	re-ranking model	31.97
5	BAAI/bge-reranker-v2-m3	29.79	40.4	7.66	32.61	568M	re-ranking model	27.62
11	mixedbread-ai/mxbai-rerank-large-v1	21.76	30.51	5.44	23.46	435M	re-ranking model	20.29

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
16	jinaai/jina-reranker-v2-base-multilingual	16.94	22.93	3.94	18.23	Unkown	sparse retrieval	15.51

Rank	Model	Comp@10	Recall@10	Prec@10	NDCG@10	Number of Parameters	Model Type	Average
16	bm25	16.94	22.93	3.94	18.23	Unkown	sparse retrieval	15.51
19	colbert	14.79	19.32	2.95	14.56	110M	dense retrieval	12.91
13	intfloat/e5-small-v2	18.6	24.86	4.17	19.01	33M	embedding model	16.66
20	facebook/contriever-msmarco	14.32	18.79	2.96	13.8	Unkown	dense retrieval	12.47
18	sentence-transformers/gtr-t5-base	15.45	20.18	3.16	15.18	110M	dense retrieval	13.49
11	sentence-transformers/gtr-t5-large	19.72	25.47	4.07	18.58	335M	dense retrieval	16.96
17	sentence-transformers/all-MiniLM-L6-v2	16.44	22.05	3.54	16.07	22M	embedding model	14.53
15	intfloat/e5-base-v2	17.58	24.38	4.29	18.59	109M	embedding model	16.21
10	intfloat/e5-large-v2	19.05	25.08	4.26	19.67	335M	embedding model	17.02
14	Alibaba-NLP/gte-base-en-v1.5	18.37	24.51	4.09	17.96	137M	embedding model	16.23
9	BAAI/bge-base-en-v1.5	19.18	25.78	4.29	19.54	109M	embedding model	17.2
8	BAAI/bge-large-en-v1.5	20.06	26.33	4.26	20.15	335M	embedding model	17.7
12	intfloat/e5-mistral-7b-instruct	19.51	25.27	4.1	18.58	7B	embedding model	16.87
7	Alibaba-NLP/gte-large-en-v1.5	21.09	27.13	4.12	22.78	434M	embedding model	18.78
3	bzantium/NV-Embed-v1	28.03	37.17	5.91	31	7.85B	embedding model	25.53
5	castorini/monot5-base-msmarco	23.66	31.29	5.19	24.47	Unkown	re-ranking model	21.15
2	jinaai/jina-reranker-v2-base-multilingual	27.95	37.17	5.96	31.44	278M	re-ranking model	25.63
1	BAAI/bge-reranker-v2-gemma	31.4	41.36	6.71	32.67	2.51B	re-ranking model	28.03
4	BAAI/bge-reranker-v2-m3	26.72	35.24	6.06	27.12	568M	re-ranking model	23.78
6	mixedbread-ai/mxbai-rerank-large-v1	22.81	29.41	4.51	21.59	435M	re-ranking model	19.58

Acknowledgement

……

This demo is created by Gradio