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    IBM Granite Vision 3.3 2b

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    Deployed on AWS
    IBM Granite Vision 3.3 2B is a compact multimodal model for accurate document image understanding, segmentation, and visual question answering.

    Overview

    IBM Granite Vision 3.3 2B is a lightweight, open-source multimodal model designed for enterprise-grade document image understanding. It excels at tasks like visual question answering, OCR, chart and table parsing, image segmentation, and structured document analysis across scanned documents, diagrams, and infographics. Built on the Granite 3.3 decoder-only LLM and enhanced with a SIGLIP2 vision encoder, it supports up to 8-page documents and generates structured outputs like doctags. Granite Vision is fine-tuned on a diverse mix of public and synthetic datasets to ensure high accuracy and robustness, especially on noisy, low-quality enterprise documents. It ranks among the top sub-7B models on OCRBench and delivers competitive results across DocVQA, TextVQA, and ChartQA. Released under Apache 2.0, it includes examples for MM-RAG, segmentation, and Hugging Face integration, and aligns with IBM's commitment to transparent, safe, and enterprise-ready AI.

    Highlights

    • Granite Vision 3.3 2B excels at understanding complex visual documents, including scanned pages, charts, diagrams, and tables. It supports visual question answering, OCR, and structured extraction through doctags. With strong performance on benchmarks like DocVQA, OCRBench, and TextVQA, it delivers accurate results even on low-quality or noisy enterprise documents, enabling reliable automation for document-heavy workflows.
    • Granite Vision 3.3 2B uses an optimized architecture combining the SIGLIP2 vision encoder and Granite 3.3 language decoder to deliver high performance with a compact 2B parameter footprint. It supports up to 8-page documents and introduces capabilities like image segmentation and doctag generation. Despite its small size, it ranks among the top open-source models under 7B parameters on OCRBench, offering strong accuracy and efficiency for real-world enterprise use cases.
    • Designed for diverse enterprise applications, Granite Vision 3.3 2B enables accurate visual understanding in workflows such as intelligent document processing, claims analysis, and compliance review. Its ability to handle complex layouts, extract structured data, and answer questions across multi-page documents makes it ideal for automating manual review tasks in industries like finance, insurance, legal, and healthcare.

    Details

    Delivery method

    Latest version

    Deployed on AWS

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    Features and programs

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    Pricing

    IBM Granite Vision 3.3 2b

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    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.

    Usage costs (10)

     Info
    Dimension
    Description
    Cost/host/hour
    ml.g5.12xlarge Inference (Batch)
    Recommended
    Model inference on the ml.g5.12xlarge instance type, batch mode
    $0.00
    ml.g6e.2xlarge Inference (Real-Time)
    Recommended
    Model inference on the ml.g6e.2xlarge instance type, real-time mode
    $0.00
    ml.g5.24xlarge Inference (Batch)
    Model inference on the ml.g5.24xlarge instance type, batch mode
    $0.00
    ml.g6e.4xlarge Inference (Real-Time)
    Model inference on the ml.g6e.4xlarge instance type, real-time mode
    $0.00
    ml.g6e.12xlarge Inference (Real-Time)
    Model inference on the ml.g6e.12xlarge instance type, real-time mode
    $0.00
    ml.g6e.16xlarge Inference (Real-Time)
    Model inference on the ml.g6e.16xlarge instance type, real-time mode
    $0.00
    ml.g6e.24xlarge Inference (Real-Time)
    Model inference on the ml.g6e.24xlarge instance type, real-time mode
    $0.00
    ml.g6e.48xlarge Inference (Real-Time)
    Model inference on the ml.g6e.48xlarge instance type, real-time mode
    $0.00
    ml.p4d.24xlarge Inference (Real-Time)
    Model inference on the ml.p4d.24xlarge instance type, real-time mode
    $0.00
    ml.p5.48xlarge Inference (Real-Time)
    Model inference on the ml.p5.48xlarge instance type, real-time mode
    $0.00

    Vendor refund policy

    This model is provided by IBM completely free of charge. No payment is required to use it. Therefore, there are no purchases to refund.

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    Usage information

     Info

    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:
    Deploy the model as an API endpoint for your applications. When you send data to the endpoint, SageMaker processes it and returns results by API response. The endpoint runs continuously until you delete it. You're billed for software and SageMaker infrastructure costs while the endpoint runs. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Deploy models for real-time inference  .
    Deploy the model to process batches of data stored in Amazon Simple Storage Service (Amazon S3). SageMaker runs the job, processes your data, and returns results to Amazon S3. When complete, SageMaker stops the model. You're billed for software and SageMaker infrastructure costs only during the batch job. Duration depends on your model, instance type, and dataset size. AWS Marketplace models don't support Amazon SageMaker Asynchronous Inference. For more information, see Batch transform for inference with Amazon SageMaker AI  .
    Version release notes

    IBM Granite Vision 3.3 2B is now available under the Apache 2.0 license for both research and commercial use. This release introduces advanced capabilities including image segmentation, structured doctag generation, and support for multi-page document processing. Built on an efficient architecture combining the Granite 3.3 decoder and SIGLIP2 vision encoder, it achieves top-tier accuracy on OCR and visual question answering benchmarks. Granite Vision 3.3 is ideal for automating document understanding in enterprise workflows across finance, healthcare, legal, and public sector domains.

    Additional details

    Inputs

    Summary

    The model can be invoked by passing a prompt. Please see the sample notebook for details.

    Input MIME type
    application/json
    https://github.com/ibm-granite-community/SageMaker/blob/main/granite-vision-3.3-2b/real_time_sample_input_data.json
    https://github.com/ibm-granite-community/SageMaker/blob/main/granite-vision-3.3-2b/batch_sample_input_data.json

    Input data descriptions

    The following table describes supported input data fields for real-time inference and batch transform.

    Field name
    Description
    Constraints
    Required
    messages
    This is the standard openAI body parameter included in the request body as part of the JSON payload for Chat models.
    -
    Yes

    Support

    Vendor support

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