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clustering benchmark

MTEB English v2 Clustering Leaderboard

MTEB English v2 Clustering is the current MTEB English v2 clustering leaderboard.

Updated Sep 8, 2026

Models100
Model coverage217
MetricOfficial leaderboard task-type mean
EvidenceA

On this page

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  • Highlights
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MTEB English v2 Clustering 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
Rank01ModelCAF2LLM-4BCodefuse AiOfficial leaderboard task-type mean68.54%Percentile100.00%Participants217EvidenceAEvaluatedN/A
Rank02ModelCAF2LLM-1.7BCodefuse AiOfficial leaderboard task-type mean64.13%Percentile99.54%Participants217EvidenceAEvaluatedN/A
Rank03ModelCAF2LLM-v2-14BCodefuse AiOfficial leaderboard task-type mean63.54%Percentile99.07%Participants217EvidenceAEvaluatedN/A
Rank04ModelCAF2LLM-v2-8BCodefuse AiOfficial leaderboard task-type mean62.85%Percentile98.61%Participants217EvidenceAEvaluatedN/A
Rank05ModelCAF2LLM-v2-4BCodefuse AiOfficial leaderboard task-type mean62.03%Percentile98.15%Participants217EvidenceAEvaluatedN/A
Rank06ModelKLQZhou-EmbeddingKingsoft LlmOfficial leaderboard task-type mean61.65%Percentile97.69%Participants217EvidenceAEvaluatedN/A
Rank07ModelCAF2LLM-v2-1.7BCodefuse AiOfficial leaderboard task-type mean60.91%Percentile97.22%Participants217EvidenceAEvaluatedN/A
Rank08ModelANgte-Qwen1.5-7B-instructAlibaba NlpOfficial leaderboard task-type mean60.91%Percentile96.76%Participants217EvidenceAEvaluatedN/A
Rank09ModelBSSeed1.5-EmbeddingBytedance SeedOfficial leaderboard task-type mean60.83%Percentile96.30%Participants217EvidenceAEvaluatedN/A
Rank10ModelNOjasper_en_vision_language_v1NovasearchOfficial leaderboard task-type mean60.52%Percentile95.83%Participants217EvidenceAEvaluatedN/A
Rank11ModelCAF2LLM-0.6BCodefuse AiOfficial leaderboard task-type mean60.36%Percentile95.37%Participants217EvidenceAEvaluatedN/A
Rank12ModelINJasper-Token-Compression-600MInfgradOfficial leaderboard task-type mean59.44%Percentile94.91%Participants217EvidenceAEvaluatedN/A
Rank13ModelGOGemini Embedding 001GoogleOfficial leaderboard task-type mean59.39%Percentile94.44%Participants217EvidenceAEvaluatedN/A
Rank14ModelSASFR-Embedding-2_RSalesforceOfficial leaderboard task-type mean59.39%Percentile93.98%Participants217EvidenceAEvaluatedN/A
Rank15ModelANLGAI-Embedding-PreviewAnnamodelsOfficial leaderboard task-type mean59.25%Percentile93.52%Participants217EvidenceAEvaluatedN/A
Rank16ModelBYSeed1.6-embeddingByteDanceOfficial leaderboard task-type mean59.22%Percentile93.06%Participants217EvidenceAEvaluatedN/A
Rank17ModelASGiga-Embeddings-instruct-10B-A1.8B-0826Ai SageOfficial leaderboard task-type mean59.07%Percentile92.59%Participants217EvidenceAEvaluatedN/A
Rank18ModelANgte-Qwen2-7B-instructAlibaba NlpOfficial leaderboard task-type mean58.97%Percentile92.13%Participants217EvidenceAEvaluatedN/A
Rank19ModelACQwen3-Embedding-8BAlibaba Cloud / Qwen TeamOfficial leaderboard task-type mean58.57%Percentile91.67%Participants217EvidenceAEvaluatedN/A
Rank20ModelJCingot-8b-r3JcornersOfficial leaderboard task-type mean58.47%Percentile91.20%Participants217EvidenceAEvaluatedN/A
Rank21ModelCAF2LLM-v2-0.6BCodefuse AiOfficial leaderboard task-type mean58.24%Percentile90.74%Participants217EvidenceAEvaluatedN/A
Rank22ModelKEKaLM-embedding-multilingual-mini-instruct-v2.5Kalm EmbeddingOfficial leaderboard task-type mean58.12%Percentile90.28%Participants217EvidenceAEvaluatedN/A
Rank23ModelASGiga-Embeddings-instruct-3B-0826Ai SageOfficial leaderboard task-type mean57.95%Percentile89.81%Participants217EvidenceAEvaluatedN/A
Rank24ModelNOstella_en_400M_v5NovasearchOfficial leaderboard task-type mean57.65%Percentile89.35%Participants217EvidenceAEvaluatedN/A
Rank25ModelACQwen3-Embedding-4BAlibaba Cloud / Qwen TeamOfficial leaderboard task-type mean57.51%Percentile88.89%Participants217EvidenceAEvaluatedN/A
Rank26ModelNOstella_en_1.5B_v5NovasearchOfficial leaderboard task-type mean57.06%Percentile88.43%Participants217EvidenceAEvaluatedN/A
Rank27ModelITBOOM_4B_v1Ict Time And QueritOfficial leaderboard task-type mean56.60%Percentile87.96%Participants217EvidenceAEvaluatedN/A
Rank28ModelGOembeddinggemma-300mGoogleOfficial leaderboard task-type mean56.55%Percentile87.50%Participants217EvidenceAEvaluatedN/A
Rank29ModelCAF2LLM-v2-330MCodefuse AiOfficial leaderboard task-type mean56.55%Percentile87.04%Participants217EvidenceAEvaluatedN/A
Rank30ModelGRGeoEmbeddingGeogpt Research ProjectOfficial leaderboard task-type mean56.50%Percentile86.57%Participants217EvidenceAEvaluatedN/A

MTEB English v2 Clustering Highlights

The leading models and scores on this benchmark.

MTEB English v2 Clustering Score Distribution

A closer view of the leading scores on this benchmark.

MTEB English v2 Clustering

The Top AI Models for MTEB English v2 Clustering

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 Clustering?

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

A benchmark for the MTEB English v2 clustering task type.

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
clustering
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 Clustering.

Which model scores highest on MTEB English v2 Clustering?

F2LLM-4B is currently ranked first with 68.54%.

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

The current leaders are F2LLM-4B (68.54%), F2LLM-1.7B (64.13%), and F2LLM-v2-14B (63.54%).

Which MTEB English v2 Clustering 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 Clustering 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 Clustering measure?

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 #1F2LLM-4B68.54%
Rank #2F2LLM-1.7B64.13%
Rank #3F2LLM-v2-14B63.54%
Rank #4F2LLM-v2-8B62.85%

Ranking basisThis mteb english v2 clustering 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
    CA
    F2LLM-4BCodefuse Ai
    Official leaderboard task-type mean
    68.54%

    Strengths

    • Ranks #1 of 217 compared models
    • 100th percentile on this benchmark
    • A evidence result

    Considerations

    • This result measures MTEB English v2 Clustering, not total model capability
  2. 02
    CA
    F2LLM-1.7BCodefuse Ai
    Official leaderboard task-type mean
    64.13%

    Strengths

    • Ranks #2 of 217 compared models
    • 100th percentile on this benchmark
    • A evidence result

    Considerations

    • This result measures MTEB English v2 Clustering, not total model capability
  3. 03
    CA
    Codefuse Ai
    Official leaderboard task-type mean
    63.54%

    Strengths

    • Ranks #3 of 217 compared models
    • 99th percentile on this benchmark
    • A evidence result

    Considerations

    • This result measures MTEB English v2 Clustering, not total model capability
  4. 04
    CA
    Codefuse Ai
    Official leaderboard task-type mean
    62.85%

    Strengths

    • Ranks #4 of 217 compared models
    • 99th percentile on this benchmark
    • A evidence result

    Considerations

    • This result measures MTEB English v2 Clustering, not total model capability
  5. 05
    CA
    Codefuse Ai
    Official leaderboard task-type mean
    62.03%

    Strengths

    • Ranks #5 of 217 compared models
    • 98th percentile on this benchmark
    • A evidence result

    Considerations

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

Selection summary

Best AI Models for MTEB English v2 Clustering

F2LLM-4B currently leads MTEB English v2 Clustering with 68.54%. 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.

F2LLM-v2-14B
F2LLM-v2-8B
F2LLM-v2-4B
Benchmark rank #1F2LLM-4B68.54%
Benchmark rank #2F2LLM-1.7B64.13%
Benchmark rank #3F2LLM-v2-14B63.54%