Embeddings
Start with 1M free tokens. Top-performing, 8192 context length bilingual embeddings for your search and RAG systems.
Interested in fine-tuned embeddings tailored to your data and use case? Let's discuss!
Embedding API
Try our world-class embedding models to improve your search and RAG systems. Start with a free trial!
upload
Request
curl https://api.jina.ai/v1/embeddings \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $JINA_API_KEY" \
-d '{
"input": ["Your text string goes here", "You can send multiple texts"],
"model": "$MODEL_NAME"
}'
download
Response
{
"model": "undefined",
"object": "list",
"usage": {
"total_tokens": 14,
"prompt_tokens": 14
},
"data": [
{
"object": "embedding",
"index": 0,
"embedding": [
-0.14528547,
-1.0152762,
...
]
},
{
"object": "embedding",
"index": 1,
"embedding": [
-0.109809875,
-0.76077706,
...
]
}
]
}
Available tokens
0
API Pricing
Our API pricing is structured around the quantity of tokens sent in the requests. This pricing model is applicable to both embedding and reranking APIs. With the same API key, you have access to both services.
Top up this API key by selecting the tokens you need
1M free tokens
Please input the right API key to top up
Choosing the Right Embeddings
Our embedding models are specifically designed to cater to diverse applications, combining language, code and multimodal representation to open up new possibilities in AI-driven solutions.
General-Purpose Embeddings
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jina-embeddings-v2-base
Bilingual Embeddings
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jina-embeddings-v2-base-de
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jina-embeddings-v2-base-zh
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jina-embeddings-v2-base-es
Code Embeddings
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jina-embeddings-v2-base-code
Leveraging deep neural networks and LLMs, our embedding models represent multimodal data into a streamlined format, improving machine comprehension, efficient storage and enabling advanced AI applications. These embeddings play a crucial role in understanding the data, enhancing user engagement, overcoming language barriers, and optimizing development processes.
Protect Your Data
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Request data and documents are not used for training models.
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Data encryption in transit (TLS 1.2+) and at rest (AES-GCM 256).
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SOC 2 and GDPR compliant.
API Integrations
Our Embedding API is natively integrated with various renowned databases, vector stores, RAG, and LLMOps frameworks. To begin, just copy and paste your API key into any of the listed integrations for a quick and seamless start.
Vector Store
LLMOps
RAG
MongoDB
DataStax
Qdrant
Pinecone
Chroma
Weaviate
Epsilla
MyScale
LlamaIndex
Haystack
Langchain
Dify
SuperDuperDB
DashVector
On-premises deployment
Deploy Jina Embeddings models in AWS Sagemaker and Microsoft Azure, and soon in Google Cloud Services, or contact our sales team to get customized Kubernetes deployments for your Virtual Private Cloud and on-premises servers.
Learning about Embeddings
Where to start with embeddings? We've got you covered. Learn about embeddings from the ground up with our comprehensive guide.
Our Publications
To understand how our large language models were trained from scratch for embedding tasks, check out our latest research and publications. Meet our team at the EMNLP, ACL, SIGIR, NeurIPS, and ICML conferences.
The Evolution of Embeddings Poster
Discover the ideal poster for your space, featuring captivating infographics or breathtaking visuals tracing the evolution of text embedding models since 1950.
FAQ
At any time, press
/
to open search barEmbeddings-related common questions
How were the jina-embeddings-v2 models trained?
How many API requests can I make per second?
Are the models behind the API open source?
Which languages do your models support?
What is the maximum length for a single sentence input?
What is the maximum number of sentences I can include in a single request?
How do Jina Embeddings models compare to OpenAI's text-embedding-ada-002 model?
How seamless is the transition from OpenAI's text-embedding-ada-002 to your solution?
Do you provide models for embedding images or audio?
Can Jina Embedding models be fine-tuned with private or company data?
Can your endpoints be hosted privately on AWS, Azure, or GCP?
API-related common questions
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Can I use the same API key for both the embedding and reranking APIs?
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Can I monitor the token usage of my API key?
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What should I do if I forget my API key?
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Do API keys expire?
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Why is the first request for some models slow?
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Is user input data used for training your models?
Billing-related common questions
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Is billing based on the number of sentences or requests?
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Is there a free trial available for new users?
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Are tokens charged for failed requests?
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What payment methods are accepted?
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Is invoicing available for token purchases?