About
The Jina AI Embeddings API offers top-performing multimodal multilingual long-context embeddings. These embeddings are designed for use in search, RAG (Retrieval Augmented Generation), and agent applications. The vendor states that the v5-omni models provide one shared embedding space for text, image, audio, and video, available in two sizes: v5-omni-small (1.6B parameters) and v5-omni-nano (0.9B parameters). Both v5-omni models are byte-for-byte compatible with v5-text. The v5-text models offer fifth-generation embedding quality in 677M small and 239M nano sizes, featuring task-specific LoRA adapters, Matryoshka dimensions, 32K context, and GGUF/MLX quantization for edge deployment. Users can select embeddings, downstream tasks for optimization via LoRA adapters, and choose to truncate inputs, specify output dimensions, apply L2 normalization, and select output data types (float, binary, or base64). The product can be purchased via subscription to the Jina Search Foundation API or deployed through cloud providers such as AWS SageMaker, Microsoft Azure, and Google Cloud.
Read from jina.ai on 2026-08-26. We describe what the vendor states; we do not audit it.
Enterprise Readiness
from cataloged dataNo compliance certifications listed
Flexible deployment: Cloud, On-Premise, Hybrid, Self-Hosted
8 documented integrations
5 documented use cases
Founded 2018 · Series A
Composite of public compliance, deployment, integration, adoption, and company signals. “Not disclosed” reflects gaps in available data, not a vendor deficiency.
Independently sourced
Pulled directly from regulator filings and platform APIs. No vendor or editorial input.
Enterprise Use Cases
Integrations
How Jina AI Embeddings compares
| Tool | Readiness | Pricing | Deployment | Compliance | Integrations |
|---|---|---|---|---|---|
| Jina AI Embeddings | 69 · Strong | Freemium | Cloud, On-Premise, Hybrid, Self-Hosted | — | 8 |
| OpenAI Enterprise | Not scored | Enterprise | Cloud | — | 5 |
| Anthropic Claude | 59 · Established | Paid | Cloud | — | 5 |
| DeepSeek | Not scored | Freemium | Cloud, Self-Hosted, On-Premise | — | 5 |
Peers from the same category, ranked by Enterprise Readiness. Readiness is a composite of cataloged compliance, deployment, integration, adoption, and company signals.
Frequently Asked Questions
What is Jina AI Embeddings used for?
Jina AI Embeddings is jina AI Embeddings provides multimodal multilingual long-context embeddings for search, RAG, and agent applications via an API. It is commonly used for semantic search for enterprise knowledge bases, ai-powered recommendation engines, customer support automation, and document classification and tagging.
Is Jina AI Embeddings free, and how is it priced?
Jina AI Embeddings offers a free tier, with paid plans that add capacity and features.
How can Jina AI Embeddings be deployed?
Jina AI Embeddings supports Cloud, On-Premise, Hybrid, and Self-Hosted deployment. On-premise and self-hosted options support data-residency and air-gapped requirements.
What does Jina AI Embeddings integrate with?
Jina AI Embeddings documents 8 integrations, including TensorFlow, PyTorch, Hugging Face, Kubernetes, AWS, and Azure.
When was Jina AI Embeddings founded?
Jina AI Embeddings was founded in 2018 and has raised $18M in funding.
Is Jina AI Embeddings enterprise-ready?
Based on cataloged data, Jina AI Embeddings has an Enterprise Readiness score of 69/100 (Strong tier), derived from its compliance, deployment, integration, adoption, and company-maturity signals.
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