Cohere Embed
Transform text and images into searchable vector representations for precise document matching and semantic discovery
- Also known as
- cohere-embed
Available worldwide
What is Cohere Embed?
An embedding and semantic search service that converts unstructured text and images into numerical vectors, enabling fast similarity search and AI-powered document ranking within your own data environment. Supports 49 languages and can be deployed on your infrastructure or via Cohere's managed cloud.
Cohere Embed pricing
We don't have Cohere Embed's full plan breakdown yet (its pricing page resisted automated reading). Here's what we could confirm. Always check live pricing for exact numbers.
Pay-as-you-go usage pricing. Free tier for testing.
What Cohere Embed 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- Web
- Cloud / SaaS
- Hybrid
- On-premise
- Self-hosted
Cohere Embed 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%
- 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%
- FastEmbedlow · 31%
Compare Cohere Embed
Side by side against other embeddings apis, attribute by attribute, with a source on every value.
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 Cohere Embed, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Pricing transparency | 80 | 0.08 | 6.7 | ✓ |
| Price level | 80 | 0.05 | 4.2 | ✓ |
| Security posture | 50 | 0.07 | 3.7 | ✓ |
| Capabilities | 67 | 0.05 | 3.3 | ✓ |
| Reliability | 0 | 0.07 | 0.0 | - |
| Integrations | 0 | 0.04 | 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 | Soc2 type ii: Yes · Pricing model: per_million_tokens_api · Architecture model: managed_cloud_api · Multi modal image and text joint embeddings: Yes · Multilingual support across 100 plus languages: Yes · Zero data retention training opt out enterprise: Yes | mediumsource · 2026-08-21 · 60% |
Market
| Attribute | Value | Evidence |
|---|---|---|
| Availability | HqCountry: CA · PrimaryMarkets: … · AvailabilityScope: global · AvailableCountries: … · NotAvailableCountries: … | highsource · 2026-08-21 · 75% |