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classification benchmark

MTEB English v2 Classification Leaderboard

MTEB English v2 Classification is the current leaderboard for MTEB(eng, v2) classification.

Updated Sep 8, 2026

Models100
Model coverage257
MetricOfficial leaderboard task-type mean
EvidenceA

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MTEB English v2 Classification Ranking

Higher official leaderboard task-type mean ranks better on this benchmark.

30 of 100 rows
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Rank
Model
Official leaderboard task-type mean
Percentile
Participants
Evidence
Evaluated
Rank01ModelTEConan-embedding-v2TencentbacOfficial leaderboard task-type mean92.23%Percentile100.00%Participants257EvidenceAEvaluatedN/A
Rank02ModelJCingot-8b-r3JcornersOfficial leaderboard task-type mean92.10%Percentile99.61%Participants257EvidenceAEvaluatedN/A
Rank03ModelVOvoyage-3-m-expVoyageaiOfficial leaderboard task-type mean90.81%Percentile99.22%Participants257EvidenceAEvaluatedN/A
Rank04ModelKLQZhou-EmbeddingKingsoft LlmOfficial leaderboard task-type mean90.70%Percentile98.83%Participants257EvidenceAEvaluatedN/A
Rank05ModelINJasper-Token-Compression-600MInfgradOfficial leaderboard task-type mean90.25%Percentile98.44%Participants257EvidenceAEvaluatedN/A
Rank06ModelASGiga-Embeddings-instruct-10B-A1.8B-0826Ai SageOfficial leaderboard task-type mean89.41%Percentile98.05%Participants257EvidenceAEvaluatedN/A
Rank07ModelANLGAI-Embedding-PreviewAnnamodelsOfficial leaderboard task-type mean89.32%Percentile97.66%Participants257EvidenceAEvaluatedN/A
Rank08ModelSASFR-Embedding-2_RSalesforceOfficial leaderboard task-type mean89.31%Percentile97.27%Participants257EvidenceAEvaluatedN/A
Rank09ModelASGiga-Embeddings-instruct-3B-0826Ai SageOfficial leaderboard task-type mean89.29%Percentile96.88%Participants257EvidenceAEvaluatedN/A
Rank10ModelNOjasper_en_vision_language_v1NovasearchOfficial leaderboard task-type mean89.21%Percentile96.48%Participants257EvidenceAEvaluatedN/A
Rank11ModelBAbge-en-iclBaaiOfficial leaderboard task-type mean89.18%Percentile96.09%Participants257EvidenceAEvaluatedN/A
Rank12ModelACQwen3-Embedding-8BAlibaba Cloud / Qwen TeamOfficial leaderboard task-type mean88.98%Percentile95.70%Participants257EvidenceAEvaluatedN/A
Rank13ModelGOGemini Embedding 001GoogleOfficial leaderboard task-type mean88.88%Percentile95.31%Participants257EvidenceAEvaluatedN/A
Rank14ModelCAF2LLM-v2-14BCodefuse AiOfficial leaderboard task-type mean88.85%Percentile94.92%Participants257EvidenceAEvaluatedN/A
Rank15ModelCAF2LLM-v2-8BCodefuse AiOfficial leaderboard task-type mean88.83%Percentile94.53%Participants257EvidenceAEvaluatedN/A
Rank16ModelBYSeed1.6-embeddingByteDanceOfficial leaderboard task-type mean88.75%Percentile94.14%Participants257EvidenceAEvaluatedN/A
Rank17ModelKINano-Em1-0.6B-v2.1KitefishaiOfficial leaderboard task-type mean88.74%Percentile93.75%Participants257EvidenceAEvaluatedN/A
Rank18ModelYILENS-d8000YibinleiOfficial leaderboard task-type mean88.72%Percentile93.36%Participants257EvidenceAEvaluatedN/A
Rank19ModelNOstella_en_1.5B_v5NovasearchOfficial leaderboard task-type mean88.70%Percentile92.97%Participants257EvidenceAEvaluatedN/A
Rank20ModelBSSeed1.5-EmbeddingBytedance SeedOfficial leaderboard task-type mean88.63%Percentile92.58%Participants257EvidenceAEvaluatedN/A
Rank21ModelCAF2LLM-v2-1.7BCodefuse AiOfficial leaderboard task-type mean88.61%Percentile92.19%Participants257EvidenceAEvaluatedN/A
Rank22ModelKEKaLM-embedding-multilingual-mini-instruct-v2.5Kalm EmbeddingOfficial leaderboard task-type mean88.57%Percentile91.80%Participants257EvidenceAEvaluatedN/A
Rank23ModelYILENS-d4000YibinleiOfficial leaderboard task-type mean88.51%Percentile91.41%Participants257EvidenceAEvaluatedN/A
Rank24ModelACQwen3-Embedding-4BAlibaba Cloud / Qwen TeamOfficial leaderboard task-type mean88.43%Percentile91.02%Participants257EvidenceAEvaluatedN/A
Rank25ModelASGiga-Embeddings-instructAi SageOfficial leaderboard task-type mean88.39%Percentile90.63%Participants257EvidenceAEvaluatedN/A
Rank26ModelCAF2LLM-v2-4BCodefuse AiOfficial leaderboard task-type mean88.39%Percentile90.23%Participants257EvidenceAEvaluatedN/A
Rank27ModelNVNV-Embed-v2NVIDIAOfficial leaderboard task-type mean87.94%Percentile89.84%Participants257EvidenceAEvaluatedN/A
Rank28ModelCAF2LLM-v2-0.6BCodefuse AiOfficial leaderboard task-type mean87.92%Percentile89.45%Participants257EvidenceAEvaluatedN/A
Rank29ModelJIjina-embeddings-v5-omni-smallJinaaiOfficial leaderboard task-type mean87.85%Percentile89.06%Participants257EvidenceAEvaluatedN/A
Rank30ModelJIjina-embeddings-v5-text-smallJinaaiOfficial leaderboard task-type mean87.85%Percentile88.67%Participants257EvidenceAEvaluatedN/A

MTEB English v2 Classification Highlights

The leading models and scores on this benchmark.

MTEB English v2 Classification Score Distribution

A closer view of the leading scores on this benchmark.

MTEB English v2 Classification

The Top AI Models for MTEB English v2 Classification

The first five results on this benchmark, with official price and output speed added where the model identity can be matched.

What is MTEB English v2 Classification?

What MTEB English v2 Classification measures and how its scores work.

MTEB English v2 Classification is a classification benchmark.

It reports the Official leaderboard task-type mean as a ratio.

Scores are shown in ratio. This benchmark is verified and has an evidence level of A.

Family
MTEB English v2
Modality
text
Primary category
classification
Score direction
higher
LLMBoard eligible
No
Evaluation key
overall

MTEB. Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about MTEB English v2 Classification.

Which model scores highest on MTEB English v2 Classification?

Conan-embedding-v2 is currently ranked first with 92.23%.

What are the top three models on MTEB English v2 Classification?

The current leaders are Conan-embedding-v2 (92.23%), ingot-8b-r3 (92.10%), and voyage-3-m-exp (90.81%).

Which MTEB English v2 Classification model has the lowest official input price?

Gemini Embedding 001 has the lowest matched official input price at $0.15 input per 1M tokens.

Which models are fastest among MTEB English v2 Classification results?

No matched runtime record is currently available.

Does the highest official leaderboard task-type mean result prove overall model quality?

No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.

What does MTEB English v2 Classification measure?

It reports the Official leaderboard task-type mean as a ratio.

Is a higher official leaderboard task-type mean better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

100 model results are currently shown.

Does this benchmark affect the overall score?

No. This benchmark is shown for reference but does not contribute to the overall score.

Rank #1Conan-embedding-v292.23%
Rank #2ingot-8b-r392.10%
Rank #3voyage-3-m-exp90.81%
Rank #4QZhou-Embedding90.70%

Ranking basisThis mteb english v2 classification AI model leaderboard uses descending official leaderboard task-type mean in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.

  1. 01
    TE
    Conan-embedding-v2Tencentbac
    Official leaderboard task-type mean
    92.23%

    Strengths

    • Ranks #1 of 257 compared models
    • 100th percentile on this benchmark
    • A evidence result

    Considerations

    • This result measures MTEB English v2 Classification, not total model capability
  2. 02
    JC
    ingot-8b-r3Jcorners
    Official leaderboard task-type mean
    92.10%

    Strengths

    • Ranks #2 of 257 compared models
    • 100th percentile on this benchmark
    • A evidence result

    Considerations

    • This result measures MTEB English v2 Classification, not total model capability
  3. 03
    VO
    Voyageai
    Official leaderboard task-type mean
    90.81%

    Strengths

    • Ranks #3 of 257 compared models
    • 99th percentile on this benchmark
    • A evidence result

    Considerations

    • This result measures MTEB English v2 Classification, not total model capability
  4. 04
    KL
    Kingsoft Llm
    Official leaderboard task-type mean
    90.70%

    Strengths

    • Ranks #4 of 257 compared models
    • 99th percentile on this benchmark
    • A evidence result

    Considerations

    • This result measures MTEB English v2 Classification, not total model capability
  5. 05
    IN
    Infgrad
    Official leaderboard task-type mean
    90.25%

    Strengths

    • Ranks #5 of 257 compared models
    • 98th percentile on this benchmark
    • A evidence result

    Considerations

    • This result measures MTEB English v2 Classification, not total model capability

Selection summary

Best AI Models for MTEB English v2 Classification

Conan-embedding-v2 currently leads MTEB English v2 Classification with 92.23%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price, and runtime.

Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.

voyage-3-m-exp
QZhou-Embedding
Jasper-Token-Compression-600M
Benchmark rank #1Conan-embedding-v292.23%
Benchmark rank #2ingot-8b-r392.10%
Benchmark rank #3voyage-3-m-exp90.81%