News
Models
Products
keyboard_arrow_down
DeepSearch
Search, read and reason until best answer found.
Reader
Convert any URL to Markdown for better grounding LLMs.
Embeddings
World-class multimodal multilingual embeddings.
Reranker
World-class reranker for maximizing search relevancy.
More
keyboard_arrow_down
Classifier
Zero-shot and few-shot classification for image and text.
Segmenter
Cut long text into chunks and do tokenization.
API Docs
Auto codegen for your copilot IDE or LLM
open_in_new
Company
keyboard_arrow_down
About us
Contact sales
Intern program
Join us
open_in_new
Download logo
open_in_new
Terms & Conditions
Log in
login

Embeddings

Top-performing multimodal multilingual long-context embeddings for search, RAG, agents applications.

Embedding API

Try our world-class embedding models to improve your search and RAG systems. Start with a free trial!
key
API Key & Billing
code
Usage
more_horiz
More
chevron_leftchevron_right
home
speedRate Limit
bug_report Raise issue
help_outlineFAQ
api
Status
chevron_leftchevron_right
Example inputs
Change them and see how the response changes!
upload
Request
curl https://api.jina.ai/v1/embeddings \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer " \
  -d @- <<EOFEOF
  {
    "normalized": true,
    "embedding_type": "float",
    "input": [
        "Organic skincare for sensitive skin with aloe vera and chamomile: Imagine the soothing embrace of nature with our organic skincare range, crafted specifically for sensitive skin. Infused with the calming properties of aloe vera and chamomile, each product provides gentle nourishment and protection. Say goodbye to irritation and hello to a glowing, healthy complexion.",
        "Bio-Hautpflege für empfindliche Haut mit Aloe Vera und Kamille: Erleben Sie die wohltuende Wirkung unserer Bio-Hautpflege, speziell für empfindliche Haut entwickelt. Mit den beruhigenden Eigenschaften von Aloe Vera und Kamille pflegen und schützen unsere Produkte Ihre Haut auf natürliche Weise. Verabschieden Sie sich von Hautirritationen und genießen Sie einen strahlenden Teint.",
        "Cuidado de la piel orgánico para piel sensible con aloe vera y manzanilla: Descubre el poder de la naturaleza con nuestra línea de cuidado de la piel orgánico, diseñada especialmente para pieles sensibles. Enriquecidos con aloe vera y manzanilla, estos productos ofrecen una hidratación y protección suave. Despídete de las irritaciones y saluda a una piel radiante y saludable.",
        "针对敏感肌专门设计的天然有机护肤产品：体验由芦荟和洋甘菊提取物带来的自然呵护。我们的护肤产品特别为敏感肌设计，温和滋润，保护您的肌肤不受刺激。让您的肌肤告别不适，迎来健康光彩。",
        "新しいメイクのトレンドは鮮やかな色と革新的な技術に焦点を当てています: 今シーズンのメイクアップトレンドは、大胆な色彩と革新的な技術に注目しています。ネオンアイライナーからホログラフィックハイライターまで、クリエイティビティを解き放ち、毎回ユニークなルックを演出しましょう。"
    ]
  }
EOFEOF

clip-v2: Multilingual Multimodal Embeddings

jina-clip-v2 is a 0.9B CLIP-style model that brings three major advances: multilingual support for 89 languages, high image resolution at 512x512, and Matryoshka representation learning for truncated embeddings.
Read Release Notearrow_forward

v3: Frontier Multilingual Embeddings

jina-embeddings-v3 is a frontier multilingual text embedding model with 570M parameters and 8192 token-length, outperforming the latest proprietary embeddings from OpenAI and Cohere on MTEB. Read our blog post and research paper below.

Three Ways to Purchase

Subscribe to our API, purchase through cloud providers, or obtain a commercial license for your organization.
radio_button_unchecked
cloud
With 3 cloud service providers
Using AWS or Azure? You can deploy our models directly on your company's cloud platform and handle billing through the CSP account.
AWS SageMaker
Embeddings
Reranker
Microsoft Azure
Embeddings
Reranker
Google Cloud
Embeddings
Reranker
radio_button_checked
With Jina Search Foundation API
The easiest way to access all of our products. Top-up tokens as you go.
Top up this API key with more tokens
Depending on your location, you may be charged in USD, EUR, or other currencies. Taxes may apply.
Please input the right API key to top up
Understand the rate limit
Rate limits are the maximum number of requests that can be made to an API within a minute per IP address/API key (RPM). Find out more about the rate limits for each product and tier below.
keyboard_arrow_down
Rate Limit
Rate limits are tracked in three ways: RPM (requests per minute), and TPM (tokens per minute). Limits are enforced per IP/API key and will be triggered when either the RPM or TPM threshold is reached first. When you provide an API key in the request header, we track rate limits by key rather than IP address.
ProductAPI EndpointDescriptionarrow_upwardw/o API Keykey_offw/ API Keykeyw/ Premium API KeykeyAverage LatencyToken Usage CountingAllowed Request
Reader APIhttps://r.jina.aiConvert URL to LLM-friendly text20 RPM500 RPMtrending_up5000 RPM7.9sCount the number of tokens in the output response.GET/POST
Reader APIhttps://s.jina.aiSearch the web and convert results to LLM-friendly textblock100 RPMtrending_up1000 RPM2.5sEvery request costs a fixed number of tokens, starting from 10000 tokensGET/POST
DeepSearchhttps://deepsearch.jina.ai/v1/chat/completionsReason, search and iterate to find the best answerblock50 RPM500 RPM56.7sCount the total number of tokens in the whole process.POST
Embedding APIhttps://api.jina.ai/v1/embeddingsConvert text/images to fixed-length vectorsblock500 RPM & 1,000,000 TPMtrending_up2,000 RPM & 5,000,000 TPM
ssid_chart
depends on the input size
help
Count the number of tokens in the input request.POST
Reranker APIhttps://api.jina.ai/v1/rerankRank documents by queryblock500 RPM & 1,000,000 TPMtrending_up2,000 RPM & 5,000,000 TPM
ssid_chart
depends on the input size
help
Count the number of tokens in the input request.POST
Classifier APIhttps://api.jina.ai/v1/trainTrain a classifier using labeled examplesblock20 RPM & 200,000 TPM60 RPM & 1,000,000 TPM
ssid_chart
depends on the input size
Tokens counted as: input_tokens × num_itersPOST
Classifier API (Few-shot)https://api.jina.ai/v1/classifyClassify inputs using a trained few-shot classifierblock20 RPM & 200,000 TPM60 RPM & 1,000,000 TPM
ssid_chart
depends on the input size
Tokens counted as: input_tokensPOST
Classifier API (Zero-shot)https://api.jina.ai/v1/classifyClassify inputs using zero-shot classificationblock200 RPM & 500,000 TPM1,000 RPM & 3,000,000 TPM
ssid_chart
depends on the input size
Tokens counted as: input_tokens + label_tokensPOST
Segmenter APIhttps://api.jina.ai/v1/segmentTokenize and segment long text20 RPM200 RPM1,000 RPM0.3sToken is not counted as usage.GET/POST
radio_button_unchecked
encrypted
With a commercial license for on-prem use
Require 100% control and privacy? Purchase a commercial license to use our models on-premises.

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.
AWS SageMaker
Embeddings
Reranker
Microsoft Azure
Embeddings
Reranker
Google Cloud
Embeddings
Reranker
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
Observability
open_in_new
MongoDB
open_in_new
DataStax
open_in_new
Qdrant
open_in_new
Pinecone
open_in_new
Chroma
open_in_new
Weaviate
open_in_new
Milvus
open_in_new
Epsilla
open_in_new
MyScale
open_in_new
LlamaIndex
open_in_new
Haystack
open_in_new
Langchain
open_in_new
Dify
open_in_new
SuperDuperDB
open_in_new
DashVector
open_in_new
Portkey
open_in_new
Baseten
open_in_new
TiDB
open_in_new
LanceDB
open_in_new
Carbon

Our Publications

Understand how our frontier search models were trained from scratch, check out our latest publications. Meet our team at EMNLP, SIGIR, ICLR, NeurIPS, and ICML!
ICLR 2025
March 04, 2025
ReaderLM-v2: Small Language Model for HTML to Markdown and JSON
arXiv
December 17, 2024
AIR-Bench: Automated Heterogeneous Information Retrieval Benchmark
ICLR 2025
December 12, 2024
jina-clip-v2: Multilingual Multimodal Embeddings for Text and Images
ECIR 2025
September 18, 2024
jina-embeddings-v3: Multilingual Embeddings With Task LoRA
arXiv
September 07, 2024
Late Chunking: Contextual Chunk Embeddings Using Long-Context Embedding Models
EMNLP 2024
August 30, 2024
Jina-ColBERT-v2: A General-Purpose Multilingual Late Interaction Retriever
WWW 2025
June 21, 2024
Leveraging Passage Embeddings for Efficient Listwise Reranking with Large Language Models
ICML 2024
May 30, 2024
Jina CLIP: Your CLIP Model Is Also Your Text Retriever
arXiv
February 26, 2024
Multi-Task Contrastive Learning for 8192-Token Bilingual Text Embeddings
arXiv
October 30, 2023
Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents
EMNLP 2023
July 20, 2023
Jina Embeddings: A Novel Set of High-Performance Sentence Embedding Models
11 publications in total.

Learning about Embeddings

Where to start with embeddings? We've got you covered. Learn about embeddings from the ground up with our comprehensive guide.

Comparison of Reranker, Vector Search, and BM25

The table below provides a comprehensive comparison of the Reranker, Vector/Embeddings Search, and BM25, highlighting their strengths and weaknesses across various categories.
RerankerVector SearchBM25
Best ForEnhanced search precision and relevanceInitial, rapid filteringGeneral text retrieval across wide-ranging queries
GranularityDetailed: Sub-document and query segmentBroad: Entire documentsIntermediate: Various text segments
Query Time ComplexityHighMediumLow
Indexing Time ComplexityNot requiredHighLow, utilizes pre-built index
Training Time ComplexityHighHighNot required
Search QualitySuperior for nuanced queriesBalanced between efficiency and accuracyConsistent and reliable for a broad set of queries
StrengthsHighly accurate with deep contextual understandingQuick and efficient, with moderate accuracyHighly scalable, with established efficacy
Try reranker API for freeTry embedding API for free

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.
Learn how we made it
shopping_cartBuy a hard copy

FAQ

How were the jina-embeddings-v3 models trained?
keyboard_arrow_down
For detailed information on our training processes, data sources, and evaluations, please refer to our technical report available on arXiv.
launcharXiv
What are the jina-clip models, and can I use them for text and image search?
keyboard_arrow_down
Jina CLIP jina-clip-v2 is an advanced multimodal embedding model that supports text-text, text-image, image-image, and image-text retrieval tasks. Unlike the original OpenAI CLIP, which struggles with text-text search, Jina CLIP excels as a text retriever. jina-clip-v2 offers a 3% performance improvement over jina-clip-v1 in both text-image and text-text retrieval tasks, supports 89 languages for multilingual image retrieval, processes higher resolution images (512x512), and reduces storage requirements with Matryoshka representations. You can read more about it in our tech report.
launcharXiv
Which languages do your models support?
keyboard_arrow_down
As of its release on September 18, 2024, jina-embeddings-v3 is the best multilingual model and ranks 2nd on the MTEB English leaderboard for models with fewer than 1 billion parameters. v3 supports a total of 89 languages, including the top 30 with the best performance: Arabic, Bengali, Chinese, Danish, Dutch, English, Finnish, French, Georgian, German, Greek, Hindi, Indonesian, Italian, Japanese, Korean, Latvian, Norwegian, Polish, Portuguese, Romanian, Russian, Slovak, Spanish, Swedish, Thai, Turkish, Ukrainian, Urdu, and Vietnamese. For more details, please refer to the jina-embeddings-v3 tech report.
launcharXiv
What is the maximum length for a single sentence input?
keyboard_arrow_down
Our models allow for an input length of up to 8192 tokens, which is significantly higher than most other models. A token can range from a single character, like 'a', to an entire word, such as 'apple'. The total number of characters that can be input depends on the length and complexity of the words used. This extended input capability enables our jina-embeddings-v3 and jina-clip models to perform more comprehensive text analysis and achieve higher accuracy in context understanding, especially for extensive textual data.
What is the maximum number of sentences I can include in a single request?
keyboard_arrow_down
A single API call can process up to 2048 sentences or texts, facilitating extensive text analysis in one request.
How do I send images to the jina-clip models?
keyboard_arrow_down
You can use either url or bytes in the input field of the API request. For url, provide the URL of the image you want to process. For bytes, encode the image in base64 format and include it in the request. The model will return the embeddings of the image in the response.
How do Jina Embeddings models compare to OpenAI's and Cohere's latest embeddings?
keyboard_arrow_down
In evaluations on the MTEB English, Multilingual, and LongEmbed benchmarks, jina-embeddings-v3 outperforms the latest proprietary embeddings from OpenAI and Cohere on English tasks, and surpasses multilingual-e5-large-instruct across all multilingual tasks. With a default output dimension of 1024, users can truncate the embedding dimensions down to 32 without sacrificing performance, thanks to the integration of Matryoshka Representation Learning (MRL).
How seamless is the transition from OpenAI's text-embedding-3-large to your solution?
keyboard_arrow_down
The transition is streamlined, as our API endpoint, matches the input and output JSON schemas of OpenAI’s text-embedding-3-large model. This compatibility ensures users can easily replace the OpenAI model with ours when using OpenAI’s endpoint.
How tokens are calculated when using jina-clip models?
keyboard_arrow_down
Tokens are calculated based on the text length and image size. For text in the request, tokens are counted in the standard way. For images, the following steps are conducted: 1. Tile Size: Each image is divided into tiles. For jina-clip-v2, tiles are 512x512 pixels, while for jina-clip-v1, tiles are 224x224 pixels. 2. Coverage: The number of tiles required to cover the input image is calculated. Even if the image dimensions are not perfectly divisible by the tile size, partial tiles are counted as full tiles. 3. Total Tiles: The total number of tiles covering the image determines the cost. For example, a 600x600 pixel image would be covered by 2x2 tiles (4 tiles) in v2 and 3x3 tiles (9 tiles) in v1. 4. Cost Calculation: For jina-clip-v2, each tile costs 4000 tokens, while for jina-clip-v1, each tile costs 1000 tokens. Example: For an image with dimensions 600x600 pixels: • With jina-clip-v2 • The image is divided into 512x512 pixel tiles. • The total number of tiles required is 2 (horizontal) x 2 (vertical) = 4 tiles. • The cost for jina-clip-v2 will be 4*4000 = 16000 tokens. • With jina-clip-v1 • The image is divided into 224x224 pixel tiles. • The total number of tiles required is 3 (horizontal) x 3 (vertical) = 9 tiles. • The cost for jina-clip-v1 will be 9*1000 = 9000 tokens.
Do you provide models for embedding images or audio?
keyboard_arrow_down
Yes, jina-clip-v2 and jina-clip-v1 can embed both images and texts. Embedding models on more modalities will be announced soon!
Can Jina Embedding models be fine-tuned with private or company data?
keyboard_arrow_down
For inquiries about fine-tuning our models with specific data, please contact us to discuss your requirements. We are open to exploring how our models can be adapted to meet your needs.
Contact
Can your endpoints be hosted privately on AWS, Azure, or GCP?
keyboard_arrow_down
Yes, our services are available on AWS, Azure, and GCP marketplaces. If you have specific requirements, please contact us at sales AT jina.ai.
launchAWS SageMakerlaunchGoogle CloudlaunchMicrosoft Azure

How to get my API key?

video_not_supported

What's the rate limit?

Rate Limit
Rate limits are tracked in three ways: RPM (requests per minute), and TPM (tokens per minute). Limits are enforced per IP/API key and will be triggered when either the RPM or TPM threshold is reached first. When you provide an API key in the request header, we track rate limits by key rather than IP address.
ProductAPI EndpointDescriptionarrow_upwardw/o API Keykey_offw/ API Keykeyw/ Premium API KeykeyAverage LatencyToken Usage CountingAllowed Request
Reader APIhttps://r.jina.aiConvert URL to LLM-friendly text20 RPM500 RPMtrending_up5000 RPM7.9sCount the number of tokens in the output response.GET/POST
Reader APIhttps://s.jina.aiSearch the web and convert results to LLM-friendly textblock100 RPMtrending_up1000 RPM2.5sEvery request costs a fixed number of tokens, starting from 10000 tokensGET/POST
DeepSearchhttps://deepsearch.jina.ai/v1/chat/completionsReason, search and iterate to find the best answerblock50 RPM500 RPM56.7sCount the total number of tokens in the whole process.POST
Embedding APIhttps://api.jina.ai/v1/embeddingsConvert text/images to fixed-length vectorsblock500 RPM & 1,000,000 TPMtrending_up2,000 RPM & 5,000,000 TPM
ssid_chart
depends on the input size
help
Count the number of tokens in the input request.POST
Reranker APIhttps://api.jina.ai/v1/rerankRank documents by queryblock500 RPM & 1,000,000 TPMtrending_up2,000 RPM & 5,000,000 TPM
ssid_chart
depends on the input size
help
Count the number of tokens in the input request.POST
Classifier APIhttps://api.jina.ai/v1/trainTrain a classifier using labeled examplesblock20 RPM & 200,000 TPM60 RPM & 1,000,000 TPM
ssid_chart
depends on the input size
Tokens counted as: input_tokens × num_itersPOST
Classifier API (Few-shot)https://api.jina.ai/v1/classifyClassify inputs using a trained few-shot classifierblock20 RPM & 200,000 TPM60 RPM & 1,000,000 TPM
ssid_chart
depends on the input size
Tokens counted as: input_tokensPOST
Classifier API (Zero-shot)https://api.jina.ai/v1/classifyClassify inputs using zero-shot classificationblock200 RPM & 500,000 TPM1,000 RPM & 3,000,000 TPM
ssid_chart
depends on the input size
Tokens counted as: input_tokens + label_tokensPOST
Segmenter APIhttps://api.jina.ai/v1/segmentTokenize and segment long text20 RPM200 RPM1,000 RPM0.3sToken is not counted as usage.GET/POST

Do I need a commercial license?

CC BY-NC License Self-Check
play_arrow
Are you using our official API or official images on Azure or AWS?
play_arrow
done
Yes
play_arrow
Are you using a paid API key or free trial key?
play_arrow
done
Paid API key
No restrictions. Use as per your current agreement.
play_arrow
info
Free API key
Free trial key can be only used for non-commercial purposes. Please purchase a paid package for commercial use.
play_arrow
Are you using our official model images on AWS and Azure?
No restrictions. Use as per your current agreement.
play_arrow
close
No
play_arrow
Are you using these models?
jina-reranker-m0
jina-clip-v2
jina-embeddings-v3
jina-reranker-v2-base-multilingual
jina-colbert-v2
reader-lm-1.5b
reader-lm-0.5b
ReaderLM-v2
play_arrow
close
No
No restrictions apply.
play_arrow
done
Yes
play_arrow
Is your use commercial?
play_arrow
question_mark
Not sure
play_arrow
Are you:
play_arrow
Using it for personal or hobby projects?
This is non-commercial. You can use the models freely.
play_arrow
A for-profit company using it internally?
This is commercial. Contact our sales team.
Contact sales
play_arrow
An educational institution using it for teaching?
This is typically non-commercial. You can use the models freely.
play_arrow
A non-profit or NGO using it for your mission?
This is typically non-commercial, but check with us if unsure.
Contact sales
play_arrow
Using it in a product or service you sell?
This is commercial. Contact our sales team.
Contact sales
play_arrow
A government entity using it for public services?
This may be commercial. Please contact us for clarification.
Contact sales
play_arrow
close
No
You can use the models freely.
play_arrow
done
Yes
Contact our sales team for licensing.
Contact sales
API-related common questions
code
Can I use the same API key for reader, embedding, reranking, classifying and fine-tuning APIs?
keyboard_arrow_down
Yes, the same API key is valid for all search foundation products from Jina AI. This includes the reader, embedding, reranking, classifying and fine-tuning APIs, with tokens shared between the all services.
code
Can I monitor the token usage of my API key?
keyboard_arrow_down
Yes, token usage can be monitored in the 'API Key & Billing' tab by entering your API key, allowing you to view the recent usage history and remaining tokens. If you have logged in to the API dashboard, these details can also be viewed in the 'Manage API Key' tab.
code
What should I do if I forget my API key?
keyboard_arrow_down
If you have misplaced a topped-up key and wish to retrieve it, please contact support AT jina.ai with your registered email for assistance. It's recommended to log in to keep your API key securely stored and easily accessible.
Contact
code
Do API keys expire?
keyboard_arrow_down
No, our API keys do not have an expiration date. However, if you suspect your key has been compromised and wish to retire it, please contact our support team for assistance. You can also revoke your key in the API Key Management dashboard.
Contact
code
Can I transfer tokens between API keys?
keyboard_arrow_down
Yes, you can transfer tokens from a premium key to another. After logging into your account on the API Key Management dashboard, use the settings of the key you want to transfer out to move all remaining paid tokens.
code
Can I revoke my API key?
keyboard_arrow_down
Yes, you can revoke your API key if you believe it has been compromised. Revoking a key will immediately disable it for all users who have stored it, and all remaining balance and associated properties will be permanently unusable. If the key is a premium key, you have the option to transfer the remaining paid balance to another key before revocation. Notice that this action cannot be undone. To revoke a key, go to the key settings in the API Key Management dashboard.
code
Why is the first request for some models slow?
keyboard_arrow_down
This is because our serverless architecture offloads certain models during periods of low usage. The initial request activates or 'warms up' the model, which may take a few seconds. After this initial activation, subsequent requests process much more quickly.
code
Is user input data used for training your models?
keyboard_arrow_down
We adhere to a strict privacy policy and do not use user input data for training our models. We are also SOC 2 Type I and Type II compliant, ensuring high standards of security and privacy.
Billing-related common questions
attach_money
Is billing based on the number of sentences or requests?
keyboard_arrow_down
Our pricing model is based on the total number of tokens processed, allowing users the flexibility to allocate these tokens across any number of sentences, offering a cost-effective solution for diverse text analysis requirements.
attach_money
Is there a free trial available for new users?
keyboard_arrow_down
We offer a welcoming free trial to new users, which includes ten millions tokens for use with any of our models, facilitated by an auto-generated API key. Once the free token limit is reached, users can easily purchase additional tokens for their API keys via the 'Buy tokens' tab.
attach_money
Are tokens charged for failed requests?
keyboard_arrow_down
No, tokens are not deducted for failed requests.
attach_money
What payment methods are accepted?
keyboard_arrow_down
Payments are processed through Stripe, supporting a variety of payment methods including credit cards, Google Pay, and PayPal for your convenience.
attach_money
Is invoicing available for token purchases?
keyboard_arrow_down
Yes, an invoice will be issued to the email address associated with your Stripe account upon the purchase of tokens.
Offices
location_on
Sunnyvale, CA
710 Lakeway Dr, Ste 200, Sunnyvale, CA 94085, USA
location_on
Berlin, Germany (HQ)
Prinzessinnenstraße 19-20, 10969 Berlin, Germany
location_on
Beijing, China
Level 5, Building 6, No.48 Haidian West St. Beijing, China
location_on
Shenzhen, China
402 Floor 4, Fu'an Technology Building, Shenzhen, China
Search Foundation
DeepSearch
Reader
Embeddings
Reranker
Classifier
Segmenter
API Documentation
Get Jina API key
Rate Limit
API Status
Company
About us
Contact sales
Newsroom
Intern program
Join us
open_in_new
Download logo
open_in_new
Terms
Security
Terms & Conditions
Privacy
Manage Cookies
email
Jina AI © 2020-2025.