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    IBM Granite 3.3 Instruct 8B

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    Deployed on AWS
    IBM Granite 3.3 Instruct 8B is an open-source model with enhanced reasoning, multilingual support, and structured output formatting.

    Overview

    IBM Granite 3.3 Instruct is an 8B parameter model optimized for instruction-following and complex reasoning. Built on Granite 3.3 Base with a 128K context window, it supports 12 languages and delivers strong performance on benchmarks like AlpacaEval-2.0 and Arena-Hard. It introduces structured thinking with clear separation between internal reasoning and final outputs. Trained on a curated mix of licensed and synthetic data and released under Apache 2.0, the model excels in summarization, QA, RAG, code generation, multilingual dialog, and long-context tasks. It also supports function-calling and fill-in-the-middle capabilities.

    Highlights

    • Granite 3.3 Instruct 8B is fine-tuned for improved reasoning and instruction-following capabilities, delivering significant gains on benchmarks like AlpacaEval-2.0 and Arena-Hard.
    • The model supports 12 languages, including English, German, Spanish, French, Japanese, Portuguese, Arabic, Czech, Italian, Korean, Dutch, and Chinese. Users can fine-tune it for additional languages beyond these.
    • Granite 3.3 Instruct 8B excels in a range of tasks such as summarization, question-answering, retrieval-augmented generation (RAG), code generation, function-calling, multilingual dialogue, fill-in-the-middle, and long-context tasks like document summarization and QA.

    Details

    Delivery method

    Latest version

    Deployed on AWS

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    Pricing

    IBM Granite 3.3 Instruct 8B

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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

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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:
    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

    The IBM Granite 3.3 Instruct 8B model is now available under the Apache 2.0 license. This 8-billion parameter model is optimized for instruction-following and complex reasoning, with a 128K context window and multilingual support. It introduces structured thinking, enabling clear separation between reasoning and output. Trained on a curated mix of licensed and synthetic data, it delivers strong performance on industry benchmarks and supports tasks such as function-calling, RAG, multilingual dialog, and fill-in-the-middle.

    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-3.3-8b-instruct/real_time_sample_input_data.json
    https://github.com/ibm-granite-community/SageMaker/blob/main/granite-3.3-8b-instruct/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
    inputs
    The prompt to be passed to the model.
    -
    Yes

    Support

    Vendor support

    Support is not provided for this product.

    AWS infrastructure support

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