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Mteb model product

baseline-random-encoder

Ranked model from MTEB.

Updated Aug 18, 2026. Default version: baseline-random-encoder

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LLMBoard Embedding Score8.5baseline-random-encoder
Coverage85%5 benchmark families
Context windowN/ATokens
Official input priceN/AOfficial price unavailable

On this page

  • Capability
  • Benchmarks
  • Arena
  • Pricing
  • Runtime
  • Specification
  • Versions
  • Compare
  • Similar models
  • About
  • FAQ

baseline-random-encoder Capability Profile

This profile uses the model's current scored version. Arena ratings and prices are shown separately.

baseline-random-encoder LLMBoard score breakdown

baseline-random-encoder Benchmark Results

Benchmark scores for baseline-random-encoder.

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Benchmark
Score
Rank
Participants
Percentile
Evidence
Evaluated
BenchmarkMTEB(eng, v2) Semantic SimilarityScore2.1%Rank207Participants207PercentileN/AEvidenceAEvaluatedAug 18, 2026
BenchmarkMTEB(eng, v2) RetrievalScore0.1%Rank208Participants208PercentileN/AEvidenceAEvaluatedAug 18, 2026
BenchmarkMTEB(eng, v2) ClusteringScore26.4%Rank212Participants213PercentileN/AEvidenceAEvaluatedAug 18, 2026
BenchmarkMTEB(eng, v2) RerankingScore30.7%Rank237Participants237PercentileN/AEvidenceAEvaluatedAug 18, 2026
BenchmarkMTEB(eng, v2) ClassificationScore20.8%Rank253Participants253PercentileN/AEvidenceAEvaluatedAug 18, 2026

baseline-random-encoder Arena Results

Preference and agent-evaluation results for the default version.

No Arena results

The default version does not have a matching Arena result yet.

baseline-random-encoder Pricing

Official vendor API pricing appears first, followed by individual provider offers.

Official API
N/A
Official provider
N/A
Lowest third-party
N/A
Tracked offerings
0
No provider prices

The default version has no current input or output token prices.

Official prices use only the vendor's configured official Provider and positive standard USD PAYG rates. Third-party offers remain explicitly labeled.

baseline-random-encoder Runtime Performance

Provider-specific output speed and catalog latency for baseline-random-encoder. Runtime does not affect the capability score.

No runtime data

No provider-specific speed or latency record is linked to the default version yet.

Browse runtime rankings

Output Speed is generated output tokens received per second. Catalog latency is reported separately from observed provider TTFT.

baseline-random-encoder Specifications

Technical details for the model's default version.

Version
baseline-random-encoder
Released
Unknown
Knowledge cutoff
Unknown
Parameters
0
Context window
N/A
Max output
N/A
Inputs
text, image, audio, video
Outputs
embedding
Open weights
Yes
License
mit

baseline-random-encoder Versions

Available versions of this model. The score column identifies the version used in the overall ranking.

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Version
Released
LLMBoard
Parameters
Context
Max output
Open weights
License
Versionbaseline-random-encoderReleasedN/ALLMBoard8.5Parameters0ContextN/AMax outputN/AOpen weightsYesLicensemit

baseline-random-encoder vs nearby models

Open a comparison with the three ranked models immediately above and below this model.

baseline-random-encodervssbert_large_nlu_rubaseline-random-encodervsdeberta-v1-basebaseline-random-encodervsternary-weight-embedding

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What is baseline-random-encoder?

Key information about baseline-random-encoder and its available data.

Ranked model from MTEB.

Data as of 2026-08-17.

FAQ

Common questions about baseline-random-encoder.

When was baseline-random-encoder released?

A release date is not available for the default version.

How much does baseline-random-encoder cost?

No official standard PAYG price is currently available for baseline-random-encoder.

Who created baseline-random-encoder?

baseline-random-encoder was created by Mteb.

What is the context window for baseline-random-encoder?

A context window is not available for the default version.

Is baseline-random-encoder open weight?

Yes. The default version is marked as open weight under mit.

How many API providers offer baseline-random-encoder?

No provider offering is currently linked to the default version.

What models should I compare baseline-random-encoder with?

Nearby ranked alternatives include sbert_large_nlu_ru, deberta-v1-base, ternary-weight-embedding.