# Text Embedding 3 Small > Source: Benchize (https://benchize.com) — https://benchize.com/models/text-embedding-3-small. When citing or reusing this content, credit "Benchize" and link to https://benchize.com/models/text-embedding-3-small. OpenAI Canonical URL: https://benchize.com/models/text-embedding-3-small Last updated: Wed, 21 Oct 2026 18:52:20 GMT Reproduction and quotation must name Benchize, link to the canonical HTML URL, and retain individual source citations. OpenAI ## Benchmarks | Benchmark | Score | Rank | | | --- | --- | --- | --- | | [FollowIR · Instruction Following](https://benchize.com/benchmarks/mteb%3AFollowIR.md) | -0.02source score | 8 / 16 | | | ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `mean_task` \| -0.02382847790034975 \| source_score \| source_published_aggregate \| Higher is better \| \| `mean_task_type` \| -0.02382847790034975 \| source_score \| source_published_aggregate \| Higher is better \| ### Configuration zeroShotPct -1 ### Reported statistics experiments Not reported rank 146 scoresByTask {"Core17InstructionRetrieval":0.011536596231932908,"News21InstructionRetrieval":-0.018085227846059017,"Robust04InstructionRetrieval":-0.06493680208692315} scoresByTaskType {"InstructionReranking":-0.02382847790034975} trainedOnTasks Not reported ### Source [Original source](https://mteb-leaderboard-backend.hf.space/v1/benchmarks/FollowIR/scores) Source MTEB Original model label openai/text-embedding-3-small Observed 2026-10-21T16:40:36.107Z Evidence SHA-256 `9727e715325c0f35c67173e5a59d96566fb3dded3f9f1558f9a7ddf230445ddb` Source locator `/rows/145` | | | | | [MTEB(Medical, v1) · Medical](https://benchize.com/benchmarks/mteb%3AMTEB(Medical%2C%20v1).md) | 0.56source score | 2 / 8 | | | ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `mean_task` \| 0.5560056744736648 \| source_score \| source_published_aggregate \| Higher is better \| \| `mean_task_type` \| 0.530734246814894 \| source_score \| source_published_aggregate \| Higher is better \| ### Configuration zeroShotPct -1 ### Reported statistics experiments Not reported rank 32 scoresByTask {"CMedQAv2-reranking":0.645397,"CUREv1":0.4684387878787879,"CmedqaRetrieval":0.21839,"MedicalQARetrieval":0.69971,"MedrxivClusteringP2P.v2":0.36448130580518867,"MedrxivClusteringS2S.v2":0.348256,"NFCorpus":0.38329,"PublicHealthQA":0.784165,"SciFact":0.73368,"SciFact-PL":0.59367,"TRECCOVID":0.77903,"TRECCOVID-PL":0.65356} scoresByTaskType {"Clustering":0.35636865290259434,"Reranking":0.645397,"Retrieval":0.5904370875420876} trainedOnTasks Not reported ### Source [Original source](https://mteb-leaderboard-backend.hf.space/v1/benchmarks/MTEB(Medical%2C%20v1)/scores) Source MTEB Original model label openai/text-embedding-3-small Observed 2026-10-21T16:40:35.852Z Evidence SHA-256 `6d1534f25189a9c84e353ced1f8d3958b2563d7c00e9719485eea3dbb0d1f13d` Source locator `/rows/31` | | | | | [MTEB(Law, v1) · Legal](https://benchize.com/benchmarks/mteb%3AMTEB(Law%2C%20v1).md) | 0.56source score | 2 / 12 | | | ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `mean_task` \| 0.5627150000000001 \| source_score \| source_published_aggregate \| Higher is better \| \| `mean_task_type` \| 0.5627150000000001 \| source_score \| source_published_aggregate \| Higher is better \| ### Configuration zeroShotPct -1 ### Reported statistics experiments Not reported rank 35 scoresByTask {"AILACasedocs":0.34899,"AILAStatutes":0.28335,"GerDaLIRSmall":0.34743,"LeCaRDv2":0.54998,"LegalBenchConsumerContractsQA":0.79147,"LegalBenchCorporateLobbying":0.93903,"LegalQuAD":0.54807,"LegalSummarization":0.6934} scoresByTaskType {"Retrieval":0.5627150000000001} trainedOnTasks Not reported ### Source [Original source](https://mteb-leaderboard-backend.hf.space/v1/benchmarks/MTEB(Law%2C%20v1)/scores) Source MTEB Original model label openai/text-embedding-3-small Observed 2026-10-21T16:40:35.593Z Evidence SHA-256 `366cc22709240d33f3a878edf79ca05670c259d3ada02601cd525a1dfb8143c1` Source locator `/rows/34` | | | | | [RTEB(Law, beta) · RTEB Legal](https://benchize.com/benchmarks/mteb%3ARTEB(Law%2C%20beta).md) | 0.47source score | 4 / 17 | | | ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `mean_task` \| 0.4684525 \| source_score \| source_published_aggregate \| Higher is better \| ### Configuration zeroShotPct -1 ### Reported statistics experiments Not reported rank 59 scoresByTask {"AILACasedocs":0.34899,"AILAStatutes":0.28335,"FrenchLegal1Retrieval":0.62906,"GermanLegal1Retrieval":0.61798,"JapaneseLegal1Retrieval":0.54799,"LegalQuAD":0.54807,"LegalSummarization":0.6934} scoresByTaskType Not reported trainedOnTasks Not reported ### Source [Original source](https://mteb-leaderboard-backend.hf.space/v1/benchmarks/RTEB(Law%2C%20beta)/scores) Source MTEB Original model label openai/text-embedding-3-small Observed 2026-10-21T16:40:41.494Z Evidence SHA-256 `7204bf17f439a2d3c2052309544ff33f53928c057dd204e20b275f942e4f5516` Source locator `/rows/58` | | | | | [RTEB(fin, beta) · RTEB Finance](https://benchize.com/benchmarks/mteb%3ARTEB(fin%2C%20beta).md) | 0.61source score | 5 / 13 | | | ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `mean_task` \| 0.6078466666666666 \| source_score \| source_published_aggregate \| Higher is better \| ### Configuration zeroShotPct -1 ### Reported statistics experiments Not reported rank 48 scoresByTask {"EnglishFinance1Retrieval":0.67313,"EnglishFinance2Retrieval":0.47823,"EnglishFinance3Retrieval":0.67377,"EnglishFinance4Retrieval":0.4721,"FinQARetrieval":0.47483,"FinanceBenchRetrieval":0.78187,"HC3FinanceRetrieval":0.56684} scoresByTaskType Not reported trainedOnTasks Not reported ### Source [Original source](https://mteb-leaderboard-backend.hf.space/v1/benchmarks/RTEB(fin%2C%20beta)/scores) Source MTEB Original model label openai/text-embedding-3-small Observed 2026-10-21T16:40:40.217Z Evidence SHA-256 `e372e75484a69b00e1a4f9619cc0d72b27ed359ea6b25f0c413f1c9551e05c7e` Source locator `/rows/47` | | | | | [MTEB(Scandinavian, v1) · Scandinavian](https://benchize.com/benchmarks/mteb%3AMTEB(Scandinavian%2C%20v1).md) | 0.58source score | 2 / 4 | | | ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `mean_task` \| 0.5836172738095238 \| source_score \| source_published_aggregate \| Higher is better \| \| `mean_task_type` \| 0.5873757092490842 \| source_score \| source_published_aggregate \| Higher is better \| ### Configuration zeroShotPct -1 ### Reported statistics experiments Not reported rank 34 scoresByTask {"AngryTweetsClassification":0.557402,"BornholmBitextMining":0.412929,"DKHateClassification":0.655319,"DalajClassification":0.50045,"DanFeverRetrieval":0.39186,"DanishPoliticalCommentsClassification":0.398265,"LccSentimentClassification":0.594,"MassiveIntentClassification":0.6399893333333333,"MassiveScenarioClassification":0.7170708333333334,"NoRecClassification":0.494141,"NorQuadRetrieval":0.23345,"NordicLangClassification":0.678933,"NorwegianCourtsBitextMining":0.924269,"NorwegianParliamentClassification":0.5585,"SNLHierarchicalClusteringP2P":0.582222,"SNLHierarchicalClusteringS2S":0.541144,"SNLRetrieval":0.92507,"ScalaClassification":0.504309,"SweFaqRetrieval":0.74101,"SweRecClassification":0.709229,"SwedishSentimentClassification":0.8918945,"SwednClusteringP2P":0.36220399999999997,"SwednClusteringS2S":0.162346,"SwednRetrieval":0.73502,"TV2Nordretrieval":0.92035,"TwitterHjerneRetrieval":0.70883,"VGHierarchicalClusteringP2P":0.430416,"VGHierarchicalClusteringS2S":0.370661} scoresByTaskType {"BitextMining":0.6685989999999999,"Classification":0.6076540512820513,"Clustering":0.40816549999999996,"Retrieval":0.6650842857142857} trainedOnTasks Not reported ### Source [Original source](https://mteb-leaderboard-backend.hf.space/v1/benchmarks/MTEB(Scandinavian%2C%20v1)/scores) Source MTEB Original model label openai/text-embedding-3-small Observed 2026-10-21T16:40:37.645Z Evidence SHA-256 `e66dff65f750060ac5843730eed4679628b45a6418b618e16473d9cc9d24aa94` Source locator `/rows/33` | | | | | [LongEmbed · Long-context Retrieval](https://benchize.com/benchmarks/mteb%3ALongEmbed.md) | 0.54source score | 2 / 13 | | | ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `mean_task` \| 0.5355016666666667 \| source_score \| source_published_aggregate \| Higher is better \| \| `mean_task_type` \| 0.5355016666666667 \| source_score \| source_published_aggregate \| Higher is better \| ### Configuration zeroShotPct -1 ### Reported statistics experiments Not reported rank 44 scoresByTask {"LEMBNarrativeQARetrieval":0.47232,"LEMBNeedleRetrieval":0.3675,"LEMBPasskeyRetrieval":0.385,"LEMBQMSumRetrieval":0.38145,"LEMBSummScreenFDRetrieval":0.92121,"LEMBWikimQARetrieval":0.68553} scoresByTaskType {"Retrieval":0.5355016666666667} trainedOnTasks Not reported ### Source [Original source](https://mteb-leaderboard-backend.hf.space/v1/benchmarks/LongEmbed/scores) Source MTEB Original model label openai/text-embedding-3-small Observed 2026-10-21T16:40:31.460Z Evidence SHA-256 `f15d7a6a931cf287269b9fe1060d2ae3f8cd2d1cc004a12b65bfc447716cc008` Source locator `/rows/43` | | | | | [RTEB(fra, beta) · RTEB French](https://benchize.com/benchmarks/mteb%3ARTEB(fra%2C%20beta).md) | 0.44source score | 7 / 17 | | | ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `mean_task` \| 0.4421545454545454 \| source_score \| source_published_aggregate \| Higher is better \| ### Configuration zeroShotPct -1 ### Reported statistics experiments Not reported rank 65 scoresByTask {"CUREv1":0.4421545454545454,"French1Retrieval":0.82459,"FrenchLegal1Retrieval":0.62906} scoresByTaskType Not reported trainedOnTasks Not reported ### Source [Original source](https://mteb-leaderboard-backend.hf.space/v1/benchmarks/RTEB(fra%2C%20beta)/scores) Source MTEB Original model label openai/text-embedding-3-small Observed 2026-10-21T16:40:40.473Z Evidence SHA-256 `ec979a256821300f551b7822b61d94415dd4bf631591e9b647f2b6ae5b4b60f4` Source locator `/rows/64` | | | | | [MTEB(fas, v2) · Persian](https://benchize.com/benchmarks/mteb%3AMTEB(fas%2C%20v2).md) | 0.55source score | 3 / 3 | | | ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `mean_task` \| 0.549018875 \| source_score \| source_published_aggregate \| Higher is better \| \| `mean_task_type` \| 0.5895871515131053 \| source_score \| source_published_aggregate \| Higher is better \| ### Configuration zeroShotPct -1 ### Reported statistics experiments Not reported rank 26 scoresByTask {"ArguAna-Fa.v2":0.33277,"BeytooteClustering":0.603813,"DeepSentiPers.v2":0.50438,"DigikalamagClassification":0.849296,"DigikalamagClustering":0.459708,"FEVER-FaHardNegatives":0.27218,"FarsTail":0.68851,"FarsiParaphraseDetection":0.948317,"Farsick":0.608489,"FiQA2018-Fa.v2":0.10107,"HamshahriClustring":0.663308,"HotpotQA-FaHardNegatives":0.2813,"MIRACLReranking":0.34765,"MIRACLRetrievalHardNegatives":0.27242,"MSMARCO-FaHardNegatives":0.47673,"MassiveIntentClassification":0.5217075,"MassiveScenarioClassification":0.566567,"NLPTwitterAnalysisClassification.v2":0.720301,"NLPTwitterAnalysisClustering":0.789225,"NQ-FaHardNegatives":0.19959,"NeuCLIR2023RetrievalHardNegatives":0.34517,"ParsinluEntail":0.574657,"ParsinluQueryParaphPC":0.770129,"PerShopDomainClassification":0.492143,"PerShopIntentClassification":0.88702,"PersianFoodSentimentClassification":0.6614990000000001,"PersianTextEmotion.v2":0.445909,"PersianWebDocumentRetrieval":0.35082,"QuoraRetrieval-Fa.v2":0.62235,"SAMSumFa":0.846083,"SCIDOCS-Fa.v2":0.08402,"SIDClassification.v2":0.527163,"SIDClustring":0.35678,"SciFact-Fa.v2":0.41255,"StyleClassification":0.622917,"SynPerChatbotConvSAClassification":0.715087,"SynPerChatbotConvSAToneChatbotClassification":0.666578,"SynPerChatbotConvSAToneUserClassification":0.603736,"SynPerChatbotRAGFAQPC":0.689606,"SynPerChatbotRAGFAQRetrieval":0.2826,"SynPerChatbotRAGSumSRetrieval":0.478077,"SynPerChatbotSatisfactionLevelClassification":0.366428,"SynPerChatbotSumSRetrieval":0.221603,"SynPerQAPC":0.905553,"SynPerQARetrieval":0.63577,"SynPerSTS":0.773342,"SynPerTextKeywordsPC":0.914576,"SynPerTextToneClassification.v3":0.728859,"TRECCOVID-Fa.v2":0.29366,"WebFAQRetrieval":0.5044,"WikipediaRerankingMultilingual":0.809355,"WikipediaRetrievalMultilingual":0.75321} scoresByTaskType {"BitextMining":0.5152543333333334,"Classification":0.6174744062499999,"Clustering":0.5745668,"PairClassification":0.7844782857142858,"Reranking":0.5785025,"Retrieval":0.36591823529411766,"STS":0.6909155} trainedOnTasks Not reported ### Source [Original source](https://mteb-leaderboard-backend.hf.space/v1/benchmarks/MTEB(fas%2C%20v2)/scores) Source MTEB Original model label openai/text-embedding-3-small Observed 2026-10-21T16:40:30.698Z Evidence SHA-256 `37f3202cf21bcdda5c3dcff6173d2b935419ec840adc6e6b32d669920b744d43` Source locator `/rows/25` | | | | | [BEIR](https://benchize.com/benchmarks/mteb%3ABEIR.md) | 0.51source score | 9 / 15 | | | ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `mean_task` \| 0.5108277999999999 \| source_score \| source_published_aggregate \| Higher is better \| \| `mean_task_type` \| 0.5108277999999999 \| source_score \| source_published_aggregate \| Higher is better \| ### Configuration zeroShotPct -1 ### Reported statistics experiments Not reported rank 102 scoresByTask {"ArguAna":0.55486,"CQADupstackRetrieval":0.425847,"ClimateFEVER":0.26856,"DBPedia":0.3997,"FEVER":0.79415,"FiQA2018":0.44909,"HotpotQA":0.63634,"MSMARCO":0.37016,"NFCorpus":0.38329,"NQ":0.52856,"QuoraRetrieval":0.88835,"SCIDOCS":0.20797,"SciFact":0.73368,"TRECCOVID":0.77903,"Touche2020":0.24283} scoresByTaskType {"Retrieval":0.5108277999999999} trainedOnTasks Not reported ### Source [Original source](https://mteb-leaderboard-backend.hf.space/v1/benchmarks/BEIR/scores) Source MTEB Original model label openai/text-embedding-3-small Observed 2026-10-21T16:40:29.416Z Evidence SHA-256 `aa692eb1a79edbe38d3f54eb90a444bff3d6c0f7b0d66e7893c86efe737c8e26` Source locator `/rows/101` | | | | | [RTEB(Health, beta) · RTEB Healthcare](https://benchize.com/benchmarks/mteb%3ARTEB(Health%2C%20beta).md) | 0.52source score | 7 / 14 | | | ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `mean_task` \| 0.5233993939393939 \| source_score \| source_published_aggregate \| Higher is better \| ### Configuration zeroShotPct -1 ### Reported statistics experiments Not reported rank 51 scoresByTask {"CUREv1":0.4684387878787879,"ChatDoctorRetrieval":0.57836,"EnglishHealthcare1Retrieval":0.53968,"GermanHealthcare1Retrieval":0.70356} scoresByTaskType Not reported trainedOnTasks Not reported ### Source [Original source](https://mteb-leaderboard-backend.hf.space/v1/benchmarks/RTEB(Health%2C%20beta)/scores) Source MTEB Original model label openai/text-embedding-3-small Observed 2026-10-21T16:40:40.988Z Evidence SHA-256 `bf62d4318f836a1a4f92c7d21e3acad553ff4cffb3162ea312270b15ce1b4e32` Source locator `/rows/50` | | | | | [RTEB(deu, beta) · RTEB German](https://benchize.com/benchmarks/mteb%3ARTEB(deu%2C%20beta).md) | 0.55source score | 4 / 17 | | | ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `mean_task` \| 0.54807 \| source_score \| source_published_aggregate \| Higher is better \| ### Configuration zeroShotPct -1 ### Reported statistics experiments Not reported rank 61 scoresByTask {"German1Retrieval":0.95885,"GermanHealthcare1Retrieval":0.70356,"GermanLegal1Retrieval":0.61798,"LegalQuAD":0.54807} scoresByTaskType Not reported trainedOnTasks Not reported ### Source [Original source](https://mteb-leaderboard-backend.hf.space/v1/benchmarks/RTEB(deu%2C%20beta)/scores) Source MTEB Original model label openai/text-embedding-3-small Observed 2026-10-21T16:40:40.727Z Evidence SHA-256 `70250aaee4788084a090cdccd91621a3c80bbf5076195bc3f215bcb392e7637d` Source locator `/rows/60` | | | | | [ChemTEB · Chemical](https://benchize.com/benchmarks/mteb%3AChemTEB.md) | 0.73source score | 2 / 13 | | | ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `mean_task` \| 0.7318446574074073 \| source_score \| source_published_aggregate \| Higher is better \| \| `mean_task_type` \| 0.5253170288235294 \| source_score \| source_published_aggregate \| Higher is better \| ### Configuration zeroShotPct -1 ### Reported statistics experiments Not reported rank 9 scoresByTask {"ChemHotpotQARetrieval":0.7836766666666667,"ChemNQRetrieval":0.57431,"PubChemAISentenceParaphrasePC":0.927259,"PubChemSMILESBitextMining":0.00242275,"PubChemSMILESPC":0.114266,"PubChemSynonymPC":0.670247,"PubChemWikiPairClassification":0.9092403333333333,"PubChemWikiParagraphsPC":0.433094,"SDSEyeProtectionClassification":0.7713,"SDSGlovesClassification":0.67045,"WikipediaBioMetChemClassification":0.99295,"WikipediaBiolumNeurochemClassification":0.968367,"WikipediaChemEngSpecialtiesClassification":0.741935,"WikipediaChemFieldsClassification":0.554994,"WikipediaChemistryTopicsClassification":0.89905,"WikipediaChemistryTopicsClustering":0.782465,"WikipediaCompChemSpectroscopyClassification":0.790045,"WikipediaCryobiologySeparationClassification":0.946352,"WikipediaCrystallographyAnalyticalClassification":0.96323,"WikipediaGreenhouseEnantiopureClassification":0.977193,"WikipediaIsotopesFissionClassification":0.908333,"WikipediaLuminescenceClassification":0.908537,"WikipediaOrganicInorganicClassification":0.888593,"WikipediaSaltsSemiconductorsClassification":0.89596,"WikipediaSolidStateColloidalClassification":0.826802,"WikipediaSpecialtiesInChemistryClustering":0.196018,"WikipediaTheoreticalAppliedClassification":0.662716} scoresByTaskType {"BitextMining":0.00242275,"Classification":0.8451062941176471,"Clustering":0.4892415,"PairClassification":0.6108212666666667,"Retrieval":0.6789933333333333} trainedOnTasks Not reported ### Source [Original source](https://mteb-leaderboard-backend.hf.space/v1/benchmarks/ChemTEB/scores) Source MTEB Original model label openai/text-embedding-3-small Observed 2026-10-21T16:40:30.425Z Evidence SHA-256 `a686e5d3d53f427eaafcd06cf50605dd45e3b4e0a7aaae31f5e8c757b4adbbed` Source locator `/rows/8` | | | | | [MTEB(spa, v1) · Spanish](https://benchize.com/benchmarks/mteb%3AMTEB(spa%2C%20v1).md) | 0.66source score | 3 / 5 | | | ### Original source values \| Metric \| Value \| Unit \| Scope \| Direction \| \| --- \| --- \| --- \| --- \| --- \| \| `mean_task` \| 0.6576181666666667 \| source_score \| source_published_aggregate \| Higher is better \| \| `mean_task_type` \| 0.6605408888888888 \| source_score \| source_published_aggregate \| Higher is better \| ### Configuration zeroShotPct -1 ### Reported statistics experiments Not reported rank 12 scoresByTask {"MIRACLReranking":0.59252,"MIRACLRetrievalHardNegatives.v2":0.51827,"MLSUMClusteringP2P":0.489102,"MLSUMClusteringS2S":0.492313,"MintakaRetrieval":0.41801,"PawsXPairClassification":0.5951044999999999,"STS17":0.8723350000000001,"STS22":0.676019,"STSBenchmarkMultilingualSTS":0.8338570000000001,"STSES":0.781869,"SpanishNewsClassification.v2":0.90332,"SpanishPassageRetrievalS2P":0.45088,"SpanishPassageRetrievalS2S":0.67756,"SpanishSentimentClassification.v2":0.889051,"XNLI":0.7199335,"XPQARetrieval":0.6117466666666668} scoresByTaskType {"Classification":0.8961855000000001,"Clustering":0.49070749999999996,"PairClassification":0.657519,"Reranking":0.59252,"Retrieval":0.5352933333333334,"STS":0.7910200000000001} trainedOnTasks Not reported ### Source [Original source](https://mteb-leaderboard-backend.hf.space/v1/benchmarks/MTEB(spa%2C%20v1)/scores) Source MTEB Original model label openai/text-embedding-3-small Observed 2026-10-21T16:40:36.375Z Evidence SHA-256 `c8eba8bf2233665c86eba5e08e282beb5d4c20ed913f54f2b53d398a89d7ffcf` Source locator `/rows/11` | | | | --- Cite as: Text Embedding 3 Small — Benchize, https://benchize.com/models/text-embedding-3-small (retrieved 2026-10-21)