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MTEB/MMTEB: multi-task multilingual embedding evaluation and efficient subsets

Contribution grade

Text embedding evaluation · Evaluation resource design

Reference score140,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Unified evaluation across embedding task types and extended it through community-reviewed multilingual tasks, caching and document/task downsampling to reduce repeated evaluation work.

Scientific scope

Unified evaluation across embedding task types and extended it through community-reviewed multilingual tasks, caching and document/task downsampling to reduce repeated evaluation work. MTEB v1 and MMTEB v1 have different task inventories and evaluation pipelines; original MTEB classification uses the stated kNN protocol. MMTEB reduced sets preserve rankings empirically for studied models, not universally for future models. Managing-team and source authorship points are not WRS effort/scoring. Incidental medical-domain texts do not constitute a medical achievement.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. MTEB v1 and MMTEB v1 have different task inventories and evaluation pipelines; original MTEB classification uses the stated kNN protocol. MMTEB reduced sets preserve rankings empirically for studied models, not universally for future models. Managing-team and source authorship points are not WRS effort/scoring. Incidental medical-domain texts do not constitute a medical achievement.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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