Sentence-Transformers
all-mpnet-base-v2
Robust and versatile embeddings for general-purpose tasks.
Strong performance on a wide range of seExcellent for sentence similarityWidely used and well-documentedEfficient for its size
Today's score
94.0
Where it ranks today
Best for / Not great for
Best for
- General semantic similarity tasks
- Text classification
- Clustering
- Building custom search applications
Not great for
- Extremely long documents without advanced handling
- Highly specialized domain-specific retrieval
- Tasks requiring the absolute highest dimensionality
Why it ranks here
Still a highly relevant and performant model, `all-mpnet-base-v2` from Sentence-Transformers remains a strong contender due to its excellent balance of performance, speed, and versatility. It's a default choice for many developers entering the embedding space and continues to perform well on a broad set of semantic understanding tasks.
30-day trend
Score breakdown
Search trends93
Benchmarks94
Developer buzz98
News mentions90
Pricing
API: $0.00 in · $0.00 out per 1M tokens · Consumer: $0.00/mo
Pricing plans
Popular
Self-hosted
Free and widely compatible.
Free
- Open source
- Works with Python/PyTorch
- Extensive documentation
- Large community
Managed Services (e.g., Cohere, Vast.ai)
Cloud deployment options.
$0 /usage
- Managed infrastructure
- Scalable
- Pay-as-you-go options
- Various providers