Sold by: Jina AI
Deployed on AWS
Embedding model for cross-modal and multimodal retrieval for text and image data
Overview
With jina-clip-v1, users have a single embedding model that delivers state-of-the-art performance in both text-only and text-image cross-modal retrieval. Jina AI has improved on OpenAI CLIP’s performance by 165% in text-only retrieval, and 12% in image-to-image retrieval, with identical or mildly better performance in text-to-image and image-to-text tasks
Highlights
- Superior performance on all combinations of modalities, and especially large improvements in text-only embedding performance.
- Support for much longer text inputs. Jina Embeddings’ 8k token input support makes it possible to process detailed textual information and correlate it with images.
- A large net savings in space, compute, code maintenance, and complexity because this multimodal model is highly performant even in non-multimodal scenarios.
Details
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Delivery method
Latest version
Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.g4dn.xlarge Inference (Batch) Recommended | Model inference on the ml.g4dn.xlarge instance type, batch mode | $1.50 |
ml.g5.xlarge Inference (Real-Time) Recommended | Model inference on the ml.g5.xlarge instance type, real-time mode | $2.50 |
ml.p2.xlarge Inference (Batch) | Model inference on the ml.p2.xlarge instance type, batch mode | $2.30 |
ml.p3.8xlarge Inference (Batch) | Model inference on the ml.p3.8xlarge instance type, batch mode | $25.00 |
ml.g4dn.4xlarge Inference (Batch) | Model inference on the ml.g4dn.4xlarge instance type, batch mode | $4.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $7.00 |
ml.g4dn.16xlarge Inference (Batch) | Model inference on the ml.g4dn.16xlarge instance type, batch mode | $14.50 |
ml.p2.8xlarge Inference (Batch) | Model inference on the ml.p2.8xlarge instance type, batch mode | $18.00 |
ml.g4dn.8xlarge Inference (Batch) | Model inference on the ml.g4dn.8xlarge instance type, batch mode | $7.60 |
ml.g4dn.12xlarge Inference (Batch) | Model inference on the ml.g4dn.12xlarge instance type, batch mode | $11.25 |
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
CLIP embedding model
Additional details
Inputs
- Summary
The model accepts JSON inputs. Input must be passed in the following format.
{ "data": [ {"text": "How is the weather today?"}, "url": "https://dummyimage.com/333/000/fff.jpg&text=embed+this " ] }
- Input MIME type
- text/csv
https://github.com/jina-ai/jina-sagemaker/blob/main/examples/sample-clip-inference-input.json
https://github.com/jina-ai/jina-sagemaker/blob/main/examples/sample-clip-batch-input.csv
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
data | String for the model to embed. | Default value: ‘’
Type: FreeText | No |
text | String for the model to embed. | Default value: ‘’
Type: FreeText | No |
data | URL to the image for the model to embed. | Default value: ‘’
Type: FreeText | No |
url | URL to the image for the model to embed. | Default value: ‘’
Type: FreeText | No |
Resources
Vendor resources
Support
Vendor support
We provide support for this model package through our enterprise support channel.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Customer reviews
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1 external reviews
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Arulmurugan K.
Performance oriented search platform out there
Reviewed on Aug 16, 2025
Review provided by G2
What do you like best about the product?
The effective embedding is multilingual and multimodal search are exceptional.
What do you dislike about the product?
It's more technical, and hence its setup is a bit harder at the beginning.
What problems is the product solving and how is that benefiting you?
it helps me to build a stable search model across the messy data points, ease of lots of time in building it.