sentence-transformers
A Python module for working with embedding and reranking models
- Also known as
- sentence-transformers
Available worldwide
What is sentence-transformers?
Python toolkit for generating semantic embeddings from text, images, audio, and video using transformer-based neural networks. Supports dense embedding models, cross-encoder rerankers for scoring and ranking, and late-interaction multi-vector models for advanced retrieval tasks.
sentence-transformers pricing
We don't have sentence-transformers's full plan breakdown yet (its pricing page resisted automated reading). Here's what we could confirm. Always check live pricing for exact numbers.
What sentence-transformers does
The capabilities that matter for embeddings apis, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.
- Architecture model
- Open weights local
- Matryoshka representation learning for dimension truncation
- -
- Multilingual support across 100 plus languages
- -
- Binary and scalar quantization for memory reduction
- -
- Cross encoder reranker API offered
- ✓
- Late interaction architecture colbert v2
- ✓
- Massive context window greater than 8k tokens
- -
- Multi modal image and text joint embeddings
- ✓
- Task specific prefixes query vs document instructions
- -
- Zero data retention training opt out enterprise
- -
- SOC2 type ii
- -
- Mit or apache permissive oss license
- -
- Pricing model
- Free open weights
Platform & deployment
Independently observed- Self-hosted
Integrations (1)
Independently observed- Hugging Face Hub
Security & compliance
Known vulnerabilities: 1 (1 in the last 12 months), max severity CRITICAL sourcea count reflects scale & disclosure, not quality
sentence-transformers FAQ
Common questions about sentence-transformers, answered from independent, dated evidence.
What is sentence-transformers?
Python toolkit for generating semantic embeddings from text, images, audio, and video using transformer-based neural networks. Supports dense embedding models, cross-encoder rerankers for scoring and ranking, and late-interaction multi-vector models for advanced retrieval tasks. It is indexed under Embeddings Apis.
Source: https://www.sbert.net
Is sentence-transformers free to use?
sentence-transformers is open source, so it can be self-hosted and used at no licence cost. It is released under the Apache-2.0 licence. Pricing changes often, so verify at source before relying on it.
Source: https://www.sbert.net
Can sentence-transformers be self-hosted?
Yes. sentence-transformers can be deployed self-hosted, so it does not have to run on the vendor's infrastructure.
Source: https://www.sbert.net
Is sentence-transformers open source?
Yes. sentence-transformers is published under the Apache-2.0 licence, a permissive licence that generally allows commercial use and modification. Licence terms can change between releases, so verify against the repository for the version you intend to use.
Source: https://github.com/huggingface/sentence-transformers
sentence-transformers alternatives
Other embeddings apis we track, ranked by the same independent score.
- Cohere EmbedNumerical representation models that convert text into embeddings for machine learning applicationsmedium · 60%
- Mixedbread (mxbai)API service for indexing and searching multimodal content with semantic capabilitiesmedium · 58%
- Amazon Bedrock Titan Embeddingslow · 35%
- FastEmbedPython library for generating text and image embeddings with minimal dependenciesmedium · 54%
- Jina EmbeddingsMultimodal vector embeddings for search, content retrieval, and AI agent developmentlow · 35%
- BAAI FlagEmbeddinglow · 45%
Compare sentence-transformers
Side by side against other embeddings apis, attribute by attribute, with a source on every value.
The vioscaleAI score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for sentence-transformers, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Development activity | 63 | 0.14 | 8.5 | ✓ |
| Release cadence | 85 | 0.08 | 6.9 | ✓ |
| Capabilities | 58 | 0.08 | 4.6 | ✓ |
| Stars | 81 | 0.05 | 3.8 | ✓ |
| Dependent projects | 62 | 0.05 | 3.3 | ✓ |
| Integrations | 9 | 0.05 | 0.5 | ✓ |
| Security posture | 0 | 0.12 | 0.0 | - |
| Package downloads | 0 | 0.04 | 0.0 | - |
| Security score | 0 | 0.05 | 0.0 | - |
| Developer Q&A activity | 0 | 0.14 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Activity
| Attribute | Value | Evidence |
|---|---|---|
| Commits last 30d | 100 | mediumsource · 2026-10-14 · 65% |
Adoption
Content
| Attribute | Value | Evidence |
|---|---|---|
| Faq | 4 items | mediumsource · 2026-09-10 · 69% |
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Pricing model: free_open_weights · Architecture model: open_weights_local · Cross encoder reranker api offered: Yes · Late interaction architecture colbert v2: Yes · Multi modal image and text joint embeddings: Yes | mediumsource · 2026-10-14 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 1 | mediumsource · 2026-08-21 · 60% |
Language
| Attribute | Value | Evidence |
|---|---|---|
| Primary | Python | highsource · 2026-10-14 · 90% |
License
| Attribute | Value | Evidence |
|---|---|---|
| Spdx | Apache-2.0 | highsource · 2026-10-14 · 95% |
Market
| Attribute | Value | Evidence |
|---|---|---|
| Availability | PrimaryMarkets: … · AvailabilityScope: global · AvailableCountries: … · NotAvailableCountries: … | highsource · 2026-08-21 · 75% |
Pricing
Release
Security
| Attribute | Value | Evidence |
|---|---|---|
| Vulnerabilities | Count: 1 · Source: https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=sentence-transformers&per_page=100 · Last 12m: 1 · Max severity: CRITICAL | highsource · 2026-10-14 · 90% |
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