Jina AI
jina.ai
What it is
Jina AI provides embeddings, rerankers, readers, and small language models for businesses and developers building search applications. Reader turns a supplied URL into clean text for language-model, retrieval-augmented generation, and agent systems; it can also search the web and return five results with URLs and content. The v5 omni embedding models accept text, images, audio, video, and PDFs in a shared vector space. Reranker v3 and v3.5 compare candidate documents with listwise scoring in one forward pass. Integrations include MongoDB, Qdrant, Pinecone, Weaviate, Milvus, LlamaIndex, Haystack, LangChain, and Dify. Model deployment is listed for AWS SageMaker, Microsoft Azure, and Google Cloud. Jina AI is available by API, on the web, and self-hosted. Free API keys allow 100 RPM and 100,000 TPM for Embeddings and Reranker; paid keys allow 500 RPM and 2,000,000 TPM. The free Toy Experiment plan includes 10 Million tokens for non-commercial use only under CC-BY-NC. One-time bundles cost $50 as a one-time purchase for Prototype Development and $500, paid once for Production Deployment.
Spec sheet
- Product
- Jina AI provides embeddings, rerankers, readers, and small language models for businesses and developers building search applications.Read 3 Oct 2026 · jina.ai
- Integrations
- The maker lists integrations including MongoDB, Qdrant, Pinecone, Weaviate, Milvus, LlamaIndex, Haystack, LangChain, and Dify.Read 3 Oct 2026 · jina.ai
- Security
- The maker's site says it is SOC 2 Type 1 and Type 2 compliant.Read 3 Oct 2026 · jina.ai
- Support
- The Production Deployment bundle includes premium customer support in 24 hours and a one-hour integration consultation.Read 3 Oct 2026 · jina.ai
- Company
- Jina AI was founded in 2020 by Han Xiao and was acquired by Elastic on October 9, 2025.Read 3 Oct 2026 · jina.ai
- Cloud platforms
- The pricing page lists model deployment through AWS SageMaker, Microsoft Azure, and Google Cloud.Read 3 Oct 2026 · jina.ai
- Data use
- The Embeddings FAQ says API requests, inputs, and outputs are not used to train Jina models.Read 3 Oct 2026 · jina.ai
- Embeddings
- The v5 omni embedding models accept text, images, audio, video, and PDFs in a shared vector space.Read 3 Oct 2026 · jina.ai
- Input limits
- Embedding model context limits vary by model from 8,192 to 32,768 tokens, and inputs above a model limit return an error unless truncation is enabled.Read 3 Oct 2026 · jina.ai
- Privacy terms
- Jina AI's legal page says product data processing is now governed by Elastic's data processing terms and directs users to Elastic's Customer DPA and Privacy Statement.Read 3 Oct 2026 · jina.ai
- Rate limits
- Free API keys are limited to 100 RPM and 100,000 TPM for Embeddings and Reranker, while paid keys allow 500 RPM and 2,000,000 TPM.Read 3 Oct 2026 · jina.ai
- Reader
- Reader extracts core content from a supplied URL and converts it into clean text for LLM, RAG, and agent systems.Read 3 Oct 2026 · jina.ai
- Reranking
- Jina reranker v3 and v3.5 use listwise scoring, comparing candidate documents against each other in one forward pass.Read 3 Oct 2026 · jina.ai
- Web search
- Reader can search the web and return the top five results with their URLs and content in LLM-friendly text.Read 3 Oct 2026 · jina.ai
Plans and prices
Strong points and limits
Strong points
- Reader extracts URL content and searches the web.
- Embeddings accept text, images, audio, video, and PDFs.
- Integrates with databases and development frameworks.
- API, web, and self-hosted options are available.
- Free plan and free trial are listed.
Limits
- Free API keys have lower rate limits.
- Toy Experiment is non-commercial only.
- Inputs beyond model context limits return an error unless truncation is enabled.
Who it suits
Jina AI suits developers and businesses building search applications with embeddings, reranking, or URL and web content extraction. Its API, web, and self-hosted options serve different deployment preferences.
Verdict
Jina AI combines content extraction, embeddings, and reranking for search-oriented applications. Check the API limits, token bundle terms, and model context limits against the intended workload.
Where Specifiction places it
- AI Search Engines#8 of 288.2