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Malenia1 model product

ternary-weight-embedding

Ranked model from MTEB.

Updated Aug 18, 2026. Default version: ternary-weight-embedding

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LLMBoard Embedding Score9.4ternary-weight-embedding
Coverage85%5 benchmark families
Context window512Tokens
Official input priceN/AOfficial price unavailable

On this page

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

ternary-weight-embedding Capability Profile

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

ternary-weight-embedding LLMBoard score breakdown

ternary-weight-embedding Benchmark Results

Benchmark scores for ternary-weight-embedding.

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Benchmark
Score
Rank
Participants
Percentile
Evidence
Evaluated
BenchmarkMTEB(eng, v2) Semantic SimilarityScore50.5%Rank202Participants207PercentileN/AEvidenceAEvaluatedAug 18, 2026
BenchmarkMTEB(eng, v2) RetrievalScore1.8%Rank207Participants208PercentileN/AEvidenceAEvaluatedAug 18, 2026
BenchmarkMTEB(eng, v2) ClusteringScore27.8%Rank211Participants213PercentileN/AEvidenceAEvaluatedAug 18, 2026
BenchmarkMTEB(eng, v2) RerankingScore35.7%Rank234Participants237PercentileN/AEvidenceAEvaluatedAug 18, 2026
BenchmarkMTEB(eng, v2) ClassificationScore51.7%Rank249Participants253PercentileN/AEvidenceAEvaluatedAug 18, 2026

ternary-weight-embedding 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.

ternary-weight-embedding 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.

ternary-weight-embedding Runtime Performance

Provider-specific output speed and catalog latency for ternary-weight-embedding. 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.

ternary-weight-embedding Specifications

Technical details for the model's default version.

Version
ternary-weight-embedding
Released
Oct 23, 2024
Knowledge cutoff
Unknown
Parameters
99M
Context window
512
Max output
N/A
Inputs
text
Outputs
embedding
Open weights
Yes
License
Unspecified

ternary-weight-embedding 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
Versionternary-weight-embeddingReleasedOct 23, 2024LLMBoard9.4Parameters99MContext512Max outputN/AOpen weightsYesLicenseUnspecified

ternary-weight-embedding vs nearby models

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

ternary-weight-embeddingvsrubert-base-casedternary-weight-embeddingvssbert_large_nlu_ruternary-weight-embeddingvsdeberta-v1-baseternary-weight-embeddingvsbaseline-random-encoder

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What is ternary-weight-embedding?

Key information about ternary-weight-embedding and its available data.

Ranked model from MTEB.

Data as of 2026-08-17.

FAQ

Common questions about ternary-weight-embedding.

When was ternary-weight-embedding released?

ternary-weight-embedding's default version was released on Oct 23, 2024.

How much does ternary-weight-embedding cost?

No official standard PAYG price is currently available for ternary-weight-embedding.

Who created ternary-weight-embedding?

ternary-weight-embedding was created by Malenia1.

What is the context window for ternary-weight-embedding?

The default version has a 512 token context window.

Is ternary-weight-embedding open weight?

Yes. The default version is marked as open weight under an unspecified license.

How many API providers offer ternary-weight-embedding?

No provider offering is currently linked to the default version.

What models should I compare ternary-weight-embedding with?

Nearby ranked alternatives include rubert-base-cased, sbert_large_nlu_ru, deberta-v1-base.