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reranking benchmark

MTEB English v2 Reranking Leaderboard

MTEB English v2 Reranking is an MTEB(eng, v2) reranking leaderboard.

Updated Sep 8, 2026

Models100
Model coverage241
MetricOfficial leaderboard task-type mean
EvidenceA

On this page

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MTEB English v2 Reranking Ranking

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

30 of 100 rows
Columns

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Rank
Model
Official leaderboard task-type mean
Percentile
Participants
Evidence
Evaluated
Rank01ModelIEYuan-embedding-2.0-enIeityuanOfficial leaderboard task-type mean53.27%Percentile100.00%Participants241EvidenceAEvaluatedN/A
Rank02ModelKLQZhou-EmbeddingKingsoft LlmOfficial leaderboard task-type mean51.77%Percentile99.58%Participants241EvidenceAEvaluatedN/A
Rank03ModelACQwen3-Embedding-8BAlibaba Cloud / Qwen TeamOfficial leaderboard task-type mean51.56%Percentile99.17%Participants241EvidenceAEvaluatedN/A
Rank04ModelJCingot-8b-r3JcornersOfficial leaderboard task-type mean50.93%Percentile98.75%Participants241EvidenceAEvaluatedN/A
Rank05ModelACQwen3-Embedding-4BAlibaba Cloud / Qwen TeamOfficial leaderboard task-type mean50.76%Percentile98.33%Participants241EvidenceAEvaluatedN/A
Rank06ModelBSSeed1.5-EmbeddingBytedance SeedOfficial leaderboard task-type mean50.67%Percentile97.92%Participants241EvidenceAEvaluatedN/A
Rank07ModelINJasper-Token-Compression-600MInfgradOfficial leaderboard task-type mean50.60%Percentile97.50%Participants241EvidenceAEvaluatedN/A
Rank08ModelANgte-Qwen2-7B-instructAlibaba NlpOfficial leaderboard task-type mean50.47%Percentile97.08%Participants241EvidenceAEvaluatedN/A
Rank09ModelCAF2LLM-v2-14BCodefuse AiOfficial leaderboard task-type mean50.32%Percentile96.67%Participants241EvidenceAEvaluatedN/A
Rank10ModelHCspeed-embedding-7b-instructHaon ChenOfficial leaderboard task-type mean50.29%Percentile96.25%Participants241EvidenceAEvaluatedN/A
Rank11ModelBYSeed1.6-embeddingByteDanceOfficial leaderboard task-type mean50.28%Percentile95.83%Participants241EvidenceAEvaluatedN/A
Rank12ModelCAF2LLM-v2-8BCodefuse AiOfficial leaderboard task-type mean50.21%Percentile95.42%Participants241EvidenceAEvaluatedN/A
Rank13ModelNOstella_en_1.5B_v5NovasearchOfficial leaderboard task-type mean50.19%Percentile95.00%Participants241EvidenceAEvaluatedN/A
Rank14ModelSASFR-Embedding-MistralSalesforceOfficial leaderboard task-type mean50.15%Percentile94.58%Participants241EvidenceAEvaluatedN/A
Rank15ModelVOvoyage-large-2-instructVoyageaiOfficial leaderboard task-type mean50.09%Percentile94.17%Participants241EvidenceAEvaluatedN/A
Rank16ModelCAF2LLM-v2-4BCodefuse AiOfficial leaderboard task-type mean50.07%Percentile93.75%Participants241EvidenceAEvaluatedN/A
Rank17ModelCAF2LLM-4BCodefuse AiOfficial leaderboard task-type mean50.05%Percentile93.33%Participants241EvidenceAEvaluatedN/A
Rank18ModelNOjasper_en_vision_language_v1NovasearchOfficial leaderboard task-type mean50.00%Percentile92.92%Participants241EvidenceAEvaluatedN/A
Rank19ModelCAF2LLM-1.7BCodefuse AiOfficial leaderboard task-type mean49.84%Percentile92.50%Participants241EvidenceAEvaluatedN/A
Rank20ModelINe5-mistral-7b-instructIntfloatOfficial leaderboard task-type mean49.78%Percentile92.08%Participants241EvidenceAEvaluatedN/A
Rank21ModelASGiga-Embeddings-instructAi SageOfficial leaderboard task-type mean49.72%Percentile91.67%Participants241EvidenceAEvaluatedN/A
Rank22ModelASGiga-Embeddings-instruct-3B-0826Ai SageOfficial leaderboard task-type mean49.62%Percentile91.25%Participants241EvidenceAEvaluatedN/A
Rank23ModelNVNV-Embed-v2NVIDIAOfficial leaderboard task-type mean49.61%Percentile90.83%Participants241EvidenceAEvaluatedN/A
Rank24ModelNOstella_en_400M_v5NovasearchOfficial leaderboard task-type mean49.60%Percentile90.42%Participants241EvidenceAEvaluatedN/A
Rank25ModelGRGritLM-7BGritlmOfficial leaderboard task-type mean49.59%Percentile90.00%Participants241EvidenceAEvaluatedN/A
Rank26ModelITICT-TIME-and-Querit-embedding-v1Ict Time And QueritOfficial leaderboard task-type mean49.53%Percentile89.58%Participants241EvidenceAEvaluatedN/A
Rank27ModelKINano-Em1-0.6B-v2.1KitefishaiOfficial leaderboard task-type mean49.49%Percentile89.17%Participants241EvidenceAEvaluatedN/A
Rank28ModelLALinq-Embed-MistralLinq Ai ResearchOfficial leaderboard task-type mean49.44%Percentile88.75%Participants241EvidenceAEvaluatedN/A
Rank29ModelJIjina-embeddings-v5-omni-smallJinaaiOfficial leaderboard task-type mean49.38%Percentile88.33%Participants241EvidenceAEvaluatedN/A
Rank30ModelJIjina-embeddings-v5-text-smallJinaaiOfficial leaderboard task-type mean49.38%Percentile87.92%Participants241EvidenceAEvaluatedN/A

MTEB English v2 Reranking Highlights

The leading models and scores on this benchmark.

MTEB English v2 Reranking Score Distribution

A closer view of the leading scores on this benchmark.

MTEB English v2 Reranking

The Top AI Models for MTEB English v2 Reranking

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 Reranking?

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

MTEB English v2 Reranking is an MTEB(eng, v2) reranking benchmark.

It measures the Official leaderboard task-type mean, reported 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
reranking
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 Reranking.

Which model scores highest on MTEB English v2 Reranking?

Yuan-embedding-2.0-en is currently ranked first with 53.27%.

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

The current leaders are Yuan-embedding-2.0-en (53.27%), QZhou-Embedding (51.77%), and Qwen3-Embedding-8B (51.56%).

Which MTEB English v2 Reranking 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 Reranking 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 Reranking measure?

It measures the Official leaderboard task-type mean, reported 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 #1Yuan-embedding-2.0-en53.27%
Rank #2QZhou-Embedding51.77%
Rank #3Qwen3-Embedding-8B51.56%
Rank #4ingot-8b-r350.93%

Ranking basisThis mteb english v2 reranking 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
    IE
    Yuan-embedding-2.0-enIeityuan
    Official leaderboard task-type mean
    53.27%

    Strengths

    • Ranks #1 of 241 compared models
    • 100th percentile on this benchmark
    • A evidence result

    Considerations

    • This result measures MTEB English v2 Reranking, not total model capability
  2. 02
    KL
    QZhou-EmbeddingKingsoft Llm
    Official leaderboard task-type mean
    51.77%

    Strengths

    • Ranks #2 of 241 compared models
    • 100th percentile on this benchmark
    • A evidence result

    Considerations

    • This result measures MTEB English v2 Reranking, not total model capability
  3. 03
    AC
    Alibaba Cloud / Qwen Team
    Official leaderboard task-type mean
    51.56%

    Strengths

    • Ranks #3 of 241 compared models
    • 99th percentile on this benchmark
    • A evidence result

    Considerations

    • This result measures MTEB English v2 Reranking, not total model capability
  4. 04
    JC
    Jcorners
    Official leaderboard task-type mean
    50.93%

    Strengths

    • Ranks #4 of 241 compared models
    • 99th percentile on this benchmark
    • A evidence result

    Considerations

    • This result measures MTEB English v2 Reranking, not total model capability
  5. 05
    AC
    Alibaba Cloud / Qwen Team
    Official leaderboard task-type mean
    50.76%

    Strengths

    • Ranks #5 of 241 compared models
    • 98th percentile on this benchmark
    • A evidence result

    Considerations

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

Selection summary

Best AI Models for MTEB English v2 Reranking

Yuan-embedding-2.0-en currently leads MTEB English v2 Reranking with 53.27%. 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.

Qwen3-Embedding-8B
ingot-8b-r3
Qwen3-Embedding-4B
Benchmark rank #1Yuan-embedding-2.0-en53.27%
Benchmark rank #2QZhou-Embedding51.77%
Benchmark rank #3Qwen3-Embedding-8B51.56%