IxI-Enki

Reference dashboard · MTEB RTEB (deu)

German embedding models for RAG

Independent preparation tool: compare public MTEB scores for retrieval, clustering and classification — updated daily via GitHub Actions. Not thesis-specific benchmark data.

MTEB Leaderboard Thesis snapshot (2026-02-16) AI Provider Landscape

Thesis citation snapshot

Frozen MTEB ranking export captured 2026-02-16 for diploma thesis citation. This is not live leaderboard data. JSON built at 2026-07-02T04:03:55.642Z.

Source: mteb_leaderboard_results_2026-02-16.csv · 162 models

# Model Mean Dim Params (B) Max tokens
1 Octen-Embedding-8B 74.05 4096 7.567 32768
2 Octen-Embedding-4B 73.25 2560 4.022 32768
3 PIXIE-Rune-v1.0 69.81 1024 0.568 6144
4 MoD-Embedding 68.53 2560 4.022 32768
5 Qwen3-Embedding-8B 66.85 4096 7.567 32768
6 Octen-Embedding-0.6B 65.66 1024 0.596 32768
7 snowflake-arctic-embed-l-v2.0 65.48 1024 0.568 8192
8 Euler-Legal-Embedding-V1 64.76 4096 7.567 1536
9 jina-embeddings-v4 63.88 2048 3.935 32768
10 inf-retriever-v1 63.22 3584 7.069 32768
11 inf-retriever-v1-1.5b 62.08 1536 1.543 32768
12 bge-m3-unsupervised 60.24 1024 0.568 8192
13 jina-embeddings-v3 59.35 1024 0.572 8194
14 BOOM_4B_v1 58.76 2560 4.022 32768
15 snowflake-arctic-embed-m-v2.0 57.95 768 0.305 8192
16 bge-m3-custom-fr 55.53 1024 0.568 8194
17 jasper_en_vision_language_v1 52.13 8960 1.565 131072
18 multilingual-e5-large-instruct 51.25 1024 0.56 514
19 bge-m3 50.36 1024 0.568 8194
20 KaLM-embedding-multilingual-mini-instruct-v1 48.76 896 0.494 512
21 Solon-embeddings-large-0.1 48.16 1024 0.56 514
22 bilingual-embedding-large 48.12 1024 0.56 514
23 multilingual-e5-base 47.85 768 0.278 514
24 multilingual-e5-small 47.80 384 0.118 512
25 gte-Qwen2-7B-instruct 46.10 3584 7.069 32768
26 USER-bge-m3 45.86 1024 0.359 8194
27 gte-Qwen2-1.5B-instruct 45.85 8960 1.543 32768
28 gte-multilingual-base 45.70 768 0.305 8192
29 bilingual-embedding-base 45.41 768 0.278 514
30 SFR-Embedding-Mistral 45.08 4096 7.111 32768
31 e5-mistral-7b-instruct 44.41 4096 7.111 32768
32 SFR-Embedding-2_R 44.24 4096 7.111 32768
33 GritLM-7B 44.18 4096 7.24 32768
34 bilingual-embedding-small 44.14 384 0.118 512
35 German_Semantic_STS_V2 43.96 1024 0.336 512
36 multilingual-e5-large 43.17 1024 0.56 514
37 KaLM-embedding-multilingual-mini-v1 41.92 896 0.494 512
38 Linq-Embed-Mistral 41.83 4096 7.111 32768
39 static-similarity-mrl-multilingual-v1 41.10 1024 0.108 —
40 stella_en_1.5B_v5 40.44 8960 1.54 131072
41 static-retrieval-mrl-en-v1 38.59 1024 0.031 —
42 gte-Qwen1.5-7B-instruct 37.99 4096 7.099 32768
43 granite-embedding-278m-multilingual 36.76 768 0.278 512
44 embedder-100p 35.31 768 0.278 514
45 Jasper-Token-Compression-600M 34.28 2048 0.607 32768
46 speed-embedding-7b-instruct 33.24 — 7.111 32768
47 granite-embedding-107m-multilingual 32.81 384 0.107 512
48 sentence_croissant_alpha_v0.4 30.96 2048 1.28 2048
49 potion-multilingual-128M 30.50 256 0.128 —
50 nomic-embed-text-v1-unsupervised 30.41 768 0.137 8192
51 jina-embedding-b-en-v1 29.87 768 0.11 512
52 sentence_croissant_alpha_v0.3 29.76 2048 1.28 2048
53 arabic-english-sts-matryoshka 28.67 1024 0.56 514
54 gte-base-en-v1.5 27.82 768 0.137 8192
55 e5-large-v2 27.18 1024 0.335 514
56 e5-large 27.15 1024 0.335 512
57 sentence_croissant_alpha_v0.2 26.98 2048 1.28 2048
58 e5-base-4k 26.90 — 0.112 4096
59 nomic-embed-text-v1 25.97 768 0.137 8192
60 nomic-embed-text-v1-ablated 25.20 768 0.137 8192
61 granite-embedding-small-english-r2 24.61 384 0.048 8192
62 jina-embedding-s-en-v1 23.62 512 0.035 512
63 granite-embedding-english-r2 23.58 768 0.149 8192
64 e5-base 22.76 768 0.109 512
65 e5-base-v2 22.32 768 0.109 512
66 stella_en_400M_v5 21.71 4096 0.435 8192
67 LLM2Vec-Mistral-7B-Instruct-v2-mntp-supervised 21.49 4096 7.153 32768
68 snowflake-arctic-embed-l 20.98 1024 0.335 512
69 NV-Embed-v1 20.70 4096 7.85 32768
70 e5-small 20.48 384 0.033 512
71 Arabic-labse-Matryoshka 20.21 768 0.471 512
72 gte-large 19.82 1024 0.335 512
73 e5-small-v2 19.67 384 0.033 512
74 bge-large-en 18.80 1024 0.335 512
75 NV-Embed-v2 18.39 4096 7.85 32768
76 paraphrase-multilingual-mpnet-base-v2 17.80 768 0.278 512
77 snowflake-arctic-embed-s 17.65 384 0.033 512
78 b1ade-embed 17.00 1024 0.335 4096
79 mmlw-e5-large 16.84 1024 0.56 514
80 Arabic-all-nli-triplet-Matryoshka 16.71 768 0.278 514
81 LaBSE 16.64 768 0.471 512
82 bge-large-en-v1.5 16.56 1024 0.335 512
83 UAE-Large-V1 16.49 1024 0.335 512
84 mxbai-embed-large-v1 16.40 1024 0.335 512
85 multi-qa-MiniLM-L6-cos-v1 16.23 384 0.023 512
86 bge-base-en 16.15 768 0.109 512
87 GIST-Embedding-v0 16.13 768 0.109 512
88 potion-base-8M 16.06 256 0.008 —
89 Ivysaur 16.05 384 0.023 512
90 bge-base-en-v1.5 16.01 768 0.109 512
91 BiCA-base 15.92 768 0.109 512
92 GIST-large-Embedding-v0 15.86 1024 0.335 512
93 gte-base 15.71 768 0.109 512
94 M2V_base_output 15.42 256 0.008 —
95 snowflake-arctic-embed-m 15.38 768 0.109 512
96 M2V_base_glove_subword 15.37 256 0.103 —
97 STS-multilingual-mpnet-base-v2 14.75 768 0.278 514
98 gte-small 14.67 384 0.033 512
99 LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse 14.60 4096 7.153 32768
100 Wartortle 14.54 384 0.017 512
101 GIST-all-MiniLM-L6-v2 14.21 384 0.023 512
102 Arabic-MiniLM-L12-v2-all-nli-triplet 13.94 384 0.118 512
103 stella-base-en-v2 13.79 — 0.109 512
104 Venusaur 13.62 384 0.016 512
105 mmlw-roberta-large 13.59 1024 0.435 514
106 Squirtle 13.44 384 0.016 512
107 paraphrase-multilingual-MiniLM-L12-v2 13.31 384 0.118 512
108 granite-embedding-125m-english 13.28 768 0.125 512
109 potion-base-4M 13.10 128 0.004 —
110 LaBSE-en-ru 12.78 768 0.129 512
111 mmlw-e5-base 12.65 768 0.278 514
112 snowflake-arctic-embed-m-v1.5 12.59 768 0.109 512
113 gte-micro-v4 12.21 384 0.019 512
114 Bulbasaur 12.16 384 0.017 512
115 LaBSE-ru-turbo 11.82 768 0.129 512
116 slx-v0.1 11.81 384 0.023 512
116 all-MiniLM-L6-v2 11.81 384 0.023 256
118 NoInstruct-small-Embedding-v0 11.79 384 0.033 512
119 bge-small-en-v1.5 11.74 512 0.033 512
120 text2vec-base-multilingual 11.71 384 0.118 256
121 M2V_multilingual_output 11.24 256 0.128 —
122 GIST-small-Embedding-v0 10.78 384 0.033 512
123 granite-embedding-30m-english 10.76 384 0.03 512
124 MedEmbed-small-v0.1 10.73 384 0.033 512
125 all-mpnet-base-v2 10.67 768 0.109 384
126 potion-base-2M 10.15 64 0.002 —
127 mmlw-roberta-base 10.11 768 0.124 514
128 snowflake-arctic-embed-xs 9.72 384 0.023 512
129 mmlw-e5-small 9.18 384 0.118 512
130 snowflake-arctic-embed-m-long 9.13 768 0.137 2048
131 nomic-embed-text-v1.5 9.01 768 0.137 8192
132 bge-base-zh-v1.5 8.79 768 0.109 512
133 gemma-2b-embeddings 8.39 2048 2.506 8192
134 gte-micro 8.21 384 0.017 512
135 sgpt-bloom-7b1-msmarco 8.15 4096 7.068 —
136 Arabic-mpnet-base-all-nli-triplet 7.91 768 0.109 514
137 all-MiniLM-L12-v2 7.44 384 0.033 256
138 ru-en-RoSBERTa 7.01 1024 0.404 512
139 bge-small-zh-v1.5 6.86 512 0.033 512
140 bge-large-zh-v1.5 6.84 1024 0.335 512
141 cai-lunaris-text-embeddings 6.34 1024 0.335 512
142 rubert-tiny 5.11 312 0.012 512
143 Arabert-all-nli-triplet-Matryoshka 4.67 768 0.135 512
144 silma-embeddding-matryoshka-v0.1 4.40 768 0.135 512
145 M2V_base_glove 4.16 256 0.102 —
146 rubert-tiny2 4.11 312 0.029 2048
147 distilrubert-small-cased-conversational 3.71 768 0.107 512
148 rubert-base-cased 3.65 768 1.28 512
149 ternary-weight-embedding 3.61 1024 0.099 512
150 USER-base 3.56 768 0.427 512
151 rubert-tiny-turbo 3.10 312 0.029 2048
152 sbert_large_nlu_ru 3.10 1024 0.427 512
153 Marbert-all-nli-triplet-Matryoshka 3.08 768 0.163 512
154 text2vec-base-chinese 3.01 768 0.102 512
155 rubert-base-cased-sentence 2.94 768 0.107 512
156 jina-embeddings-v2-small-en 2.89 512 0.033 8192
157 sbert_large_mt_nlu_ru 2.60 1024 0.427 512
158 jina-embeddings-v2-base-en 2.60 768 0.137 8192
159 random-encoder-baseline 2.53 32 — —
160 deberta-v1-base 2.11 768 0.124 512
161 Qwen3-Embedding-0.6B — 1024 0.596 32768
161 Qwen3-Embedding-4B — 2560 4.022 32768

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