Jina AI supplies search components for teams building applications with language models. Its offerings include embeddings, rerankers, Reader, and small language models, with access through an API, the web, or self-hosted software. Reader turns a supplied URL into clean text for LLM, retrieval-augmented generation, and agent systems; it can also search the web and return five results with their URLs and content. The v5 omni embedding models place text, images, audio, video, and PDFs in a shared vector space. Reranker v3 and v3.5 compare candidate documents using listwise scoring in one forward pass. The listed integrations include MongoDB, Qdrant, Pinecone, Weaviate, Milvus, LlamaIndex, Haystack, LangChain, and Dify. Model deployment is listed for AWS SageMaker, Microsoft Azure, and Google Cloud. Free API keys for Embeddings and Reranker allow 100 RPM and 100,000 TPM; paid keys allow 500 RPM and 2,000,000 TPM. Embedding context limits vary by model from 8,192 to 32,768 tokens. Inputs above a model's limit return an error unless truncation is enabled. Jina AI says it is SOC 2 Type 1 and Type 2 compliant, and its Embeddings FAQ says API requests, inputs, and outputs are not used to train its models.
Who it is for
Jina AI suits developers and businesses building search applications that use language models, especially those needing embeddings, document reranking, or URL content extraction. Its API, web, and self-hosted options and listed database and framework integrations support different deployment setups.
What is good
- Reader extracts URL content into clean text for LLM and retrieval systems.
- Reader can return five web search results with URLs and content.
- v5 omni embeddings accept text, images, audio, video, and PDFs.
- Integrations include MongoDB, Qdrant, Pinecone, and LangChain.
- The maker states SOC 2 Type 1 and Type 2 compliance.
What to know first
- Toy Experiment permits non-commercial use only under CC-BY-NC.
- Free Embeddings and Reranker keys are limited to 100 RPM and 100,000 TPM.
- Embedding inputs above a model's context limit error unless truncation is enabled.
- Prototype Development costs 50.00 USD per once; Production Deployment costs 500.00 USD per once.
Verdict
Choose Jina AI if you are building search applications and need its embedding, reranking, or Reader capabilities across API, web, or self-hosted access. The free Toy Experiment plan is limited to non-commercial use, while the listed paid options are one-time token bundles.
Get started with Jina AI
- Visit https://jina.ai/.
- Choose API, self-hosted, or web access.
- Choose the free Toy Experiment plan or a listed paid token bundle.
- For cloud model deployment, use AWS SageMaker, Microsoft Azure, or Google Cloud.
What the free plan stops at
Toy Experiment provides 10 Million tokens for non-commercial use only under CC-BY-NC. Free API keys for Embeddings and Reranker are limited to 100 RPM and 100,000 TPM. Embedding context limits vary from 8,192 to 32,768 tokens, and inputs above the selected model's limit return an error unless truncation is enabled.
Questions about Jina AI
Does Jina AI have a free plan?
Yes. Toy Experiment is free and includes 10 Million tokens for non-commercial use only under CC-BY-NC.
What do the paid plans cost?
Prototype Development is 50.00 USD per once, billed $50, and includes 1 Billion tokens. Production Deployment is 500.00 USD per once, billed $500, and includes 11 Billion tokens.
Which platforms can I use?
Jina AI lists API, self-hosted, and web platforms. Its pricing page also lists model deployment through AWS SageMaker, Microsoft Azure, and Google Cloud.
What integrations are listed?
The maker lists MongoDB, Qdrant, Pinecone, Weaviate, Milvus, LlamaIndex, Haystack, LangChain, and Dify.
Who makes Jina AI?
Jina AI was founded in 2020 by Han Xiao and was acquired by Elastic on October 9, 2025.
Is there a free trial?
Yes, a free trial is listed.
Jina AI plans and pricing
All plansCompared on AI search engines
- Free plan
- Yes
- Citation format
- mixed
- Deep research mode
- Yes
- Source filters
- Yes
- API access
- Yes
