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Mcgill Nlp model product

LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse

LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse is an embedding model from Mcgill Nlp ranked on MTEB.

Updated Sep 8, 2026. Default version: LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse

LLMBoard Embedding Score29.6LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse
Coverage85%5 benchmark families
Context window32.8KTokens
Official input priceN/AOfficial price unavailable

On this page

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

LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse Capability Profile

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

LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse LLMBoard score breakdown

LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse Benchmark Results

Benchmark scores for LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse.

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Benchmark
Score
Rank
Participants
Percentile
Evidence
Evaluated
BenchmarkMTEB English v2 Semantic SimilarityScore78.24%Rank143Participants211Percentile32.38%EvidenceAEvaluatedN/A
BenchmarkMTEB English v2 ClassificationScore78.33%Rank167Participants257Percentile35.16%EvidenceAEvaluatedN/A
BenchmarkMTEB English v2 ClusteringScore40.74%Rank168Participants217Percentile22.69%EvidenceAEvaluatedN/A
BenchmarkMTEB English v2 RetrievalScore31.05%Rank172Participants212Percentile18.96%EvidenceAEvaluatedN/A
BenchmarkMTEB English v2 RerankingScore44.17%Rank184Participants241Percentile23.75%EvidenceAEvaluatedN/A

LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse 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.

LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse 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.

LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse Runtime Performance

Provider-specific output speed and catalog latency for LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse. Runtime does not affect the capability score.

No runtime data

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

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

LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse Specifications

Technical details for the model's default version.

Version
LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse
Released
Apr 9, 2024
Knowledge cutoff
Unknown
Parameters
7.2B
Context window
32.8K
Max output
N/A
Inputs
text
Outputs
embedding
Open weights
Yes
License
mit

LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse 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
VersionLLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcseReleasedApr 9, 2024LLMBoard29.56Parameters7.2BContext32.8KMax outputN/AOpen weightsYesLicensemit

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Details

What is LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse?

Key information about LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse and its available data.

LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse is an embedding model from Mcgill Nlp. It is a ranked model from MTEB.

Data as of 2026-09-08.

FAQ

Common questions about LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse.

When was LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse released?

LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse's default version was released on Apr 9, 2024.

How much does LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse cost?

No official standard PAYG price is currently available for LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse.

Who created LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse?

LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse was created by Mcgill Nlp.

What is the context window for LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse?

The default version has a 32.8K token context window.

Is LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse open weight?

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

How many API providers offer LLM2Vec-Mistral-7B-Instruct-v2-mntp-unsup-simcse?

No provider offering is currently linked to the default version.

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