Google Vertex AI Text Embeddings
Convert text into dense vector representations that capture semantic meaning for retrieval and similarity tasks
- Also known as
- google-vertex-ai-text-embeddings
Available worldwide · Popular in: US
What is Google Vertex AI Text Embeddings?
A cloud-based API that transforms text into high-dimensional vector embeddings using deep learning. Supports multiple languages and task types, integrating with vector databases for efficient semantic search.
Google Vertex AI Text Embeddings pricing
We don't have Google Vertex AI Text Embeddings's full plan breakdown yet (its pricing page resisted automated reading). Here's what we could confirm. Always check live pricing for exact numbers.
Free credits ($300) for new customers; usage-based pricing thereafter
What Google Vertex AI Text Embeddings 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
- Managed cloud API
- 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
- Per million tokens API
Platform & deployment
Independently observed- CLI
- Web
- Cloud / SaaS
Integrations (1)
Independently observed- Vector Search
Google Vertex AI Text Embeddings alternatives
Other embeddings apis we track, ranked by the same independent score.
- Mixedbread (mxbai)Strengthen AI agent performance through efficient multi-format data retrievallow · 35%
- Cohere EmbedTransform text and images into searchable vector representations for precise document matching and semantic discoverylow · 45%
- BAAI FlagEmbeddinglow · 27%
- Amazon Bedrock Titan Embeddingslow · 21%
- sentence-transformerslow · 32%
- Jina EmbeddingsEmbeddings API for multimodal, multilingual content that powers search, retrieval-augmented generation, and AI applicationslow · 36%
The Vioscale 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 Google Vertex AI Text Embeddings, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Price level | 80 | 0.05 | 4.2 | ✓ |
| Capabilities | 67 | 0.05 | 3.3 | ✓ |
| Pricing transparency | 25 | 0.08 | 2.1 | ✓ |
| Integrations | 9 | 0.04 | 0.4 | ✓ |
| Reliability | 0 | 0.07 | 0.0 | - |
| Security posture | 0 | 0.07 | 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.
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Pricing model: per_million_tokens_api · Architecture model: managed_cloud_api · Multi modal image and text joint embeddings: Yes · Massive context window greater than 8k tokens: Yes · Multilingual support across 100 plus languages: Yes · Task specific prefixes query vs document instructions: Yes | mediumsource · 2026-08-21 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 1 | mediumsource · 2026-08-21 · 60% |
Market
| Attribute | Value | Evidence |
|---|---|---|
| Availability | PrimaryMarkets: … · AvailabilityScope: global · AvailableCountries: … · NotAvailableCountries: … | mediumsource · 2026-08-21 · 50% |