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IBM Granite 3.2 Instruct is an open-source model with controllable reasoning, offering strong performance and enhanced complex thinking.
Overview
IBM Granite 3.2 Instruct is a family of 2B and 8B parameter language models fine-tuned for enhanced reasoning capabilities. Built on Granite 3.1, it uses permissively licensed open-source datasets and synthetic data optimized for reasoning tasks. A key feature is its controllable thinking capability, which can be toggled on or off to optimize computational efficiency. Released under Apache 2.0, it supports 12 languages, including English, German, Spanish, French, Japanese, and Chinese, with extensibility for additional languages. Unlike industry trends that separate reasoning models, IBM integrates reasoning directly into the core Instruct models. While traditional approaches improve logic-based tasks at the cost of others, IBM’s method enhances reasoning without trade-offs. It excels in summarization, classification, extraction, QA, RAG, code tasks, function-calling, and multilingual dialogues, performing strongly on prominent benchmarks without sacrificing other capabilities.
Highlights
- IBM Granite 3.2 introduces controllable reasoning capabilities that can be toggled on or off with a simple parameter, allowing developers to balance computational efficiency with enhanced problem-solving. This unique approach preserves general performance while significantly improving complex instruction following.
- Unlike competing reasoning models that sacrifice general capabilities for narrow domains, Granite 3.2 demonstrates substantial improvements on benchmarks like ArenaHard and AlpacaEval without compromising performance elsewhere, maintaining IBM's commitment to safety and comprehensive functionality.
- Granite 3.2 applies IBM's Thought Preference Optimization framework to enhance reasoning without the extensive computation typically required by other models. This practical approach delivers enterprise-ready performance across summarization, classification, RAG, code tasks, and multilingual support in 12 languages.
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.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.12xlarge Inference (Real-Time) | Model inference on the ml.g6e.12xlarge instance type, real-time 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.24xlarge Inference (Real-Time) | Model inference on the ml.g6e.24xlarge 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.g6e.48xlarge Inference (Real-Time) | Model inference on the ml.g6e.48xlarge 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.p5.48xlarge Inference (Real-Time) | Model inference on the ml.p5.48xlarge instance type, real-time mode | $0.00 |
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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
IBM Granite 3.2 Instruct is a reasoning-enhanced model in 2B and 8B sizes, built on Granite 3.1. Trained on permissive and synthetic reasoning data, it allows developers to toggle its reasoning process on and off via a simple parameter. Unlike other models, Granite 3.2 improves complex instruction following without sacrificing general performance. It excels in summarization, classification, QA, RAG, coding, and function calling. Supporting 12 languages, it is ideal for enterprise use where strong reasoning and efficiency are key.
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-3.2-2b-instruct/real_time_sample_input_data.json
https://github.com/ibm-granite-community/SageMaker/blob/main/granite-3.2-2b-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 |
Resources
Support
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