Today, at IBM’s (NYSE: IBM) annual TechXchange event, the company announced the release of its most advanced family of AI models to date, Granite 3.0. IBM’s third-generation Granite flagship language models can outperform or match similarly sized models from leading model providers on many academic and industry benchmarks, showcasing strong performance, transparency and safety.
Consistent with the company’s commitment to open-source AI, the Granite models are released under the permissive Apache 2.0 license, making them unique in the combination of performance, flexibility and autonomy they provide to enterprise clients and the community at large.
The new Granite 3.0 8B and 2B language models are designed as ‘workhorse’ models for enterprise AI, designed to be fine-tuned with enterprise data and seamlessly integrated across diverse business environments or workflows.
While many large language models (LLMs) are trained on publicly available data, a vast majority of enterprise data remains untapped. By combining a small Granite model with enterprise data, especially using the revolutionary alignment technique InstructLab – introduced by IBM and RedHat in May – IBM believes businesses can achieve task-specific performance that rivals larger models at a fraction of the cost.
The Granite 3.0 release reaffirms IBM’s commitment to building transparency, safety, and trust in AI products. The Granite 3.0 technical report and responsible use guide provide a description of the datasets used to train these models, details of the filtering, cleansing, and curation steps applied, along with comprehensive results of model performance across major academic and enterprise benchmarks.
Critically, IBM provides an IP indemnity for all Granite models on watsonx.ai so enterprise clients can be more confident in merging their data with the models.
Raising the bar: Granite 3.0 benchmarks
The Granite 3.0 language models also demonstrate promising results on raw performance.
The Granite 3.0 models were trained on over 12 trillion tokens on data taken from 12 different natural languages and 116 different programming languages, using a novel two-stage training method, leveraging results from several thousand experiments designed to optimize data quality, data selection, and training parameters.
IBM is also announcing an updated release of its pre-trained Granite Time Series models, the first versions of which were released earlier this year. These new models are trained on 3 times more data and deliver strong performance on major time series benchmarks.
Introducing Granite Guardian 3.0: ushering the next era of responsible AI
IBM is also introducing a new family of Granite Guardian models that permit application developers to implement safety guardrails by checking user prompts and LLM responses for a variety of risks. The Granite Guardian 3.0 8B and 2B models provide the most comprehensive set of risk and harm detection capabilities available in the market today.
In addition to harm dimensions such as social bias, hate, toxicity, profanity, violence, jailbreaking and more, these models also provide a range of unique RAG-specific checks such as groundedness, context relevance, and answer relevance.
While the Granite Guardian models are derived from the corresponding Granite language models, they can be used to implement guardrails alongside any open or proprietary AI models.
Assistants to Agents: realizing the future for enterprise AI
IBM is advancing enterprise AI through a spectrum of technologies – from models and assistants, to the tools needed to tune and deploy AI specifically for companies’ unique data and use-cases. IBM is also paving the way for future AI agents that can self-direct, reflect, and perform complex tasks in dynamic business environments.
IBM continues to evolve its portfolio of AI assistant technologies – from watsonx Orchestrate to help companies build their own assistants via low-code tooling and automation, to a wide set of pre-built assistants for specific tasks and domains such as customer service, human resources, sales, and marketing.
Today IBM also unveiled the upcoming release of the next generation of watsonx Code Assistant, powered by Granite code models, to offer general-purpose coding assistance across languages like C, C++, Go, Java, and Python, with advanced application modernization capabilities for Enterprise Java Applications.
IBM also plans to release new tools to help developers build, customize and deploy AI more efficiently via watsonx.ai – including agentic frameworks, integrations with existing environments and low-code automations for common use-cases like RAG and agents.
IBM is focused on developing AI agent technologies which are capable of greater autonomy, sophisticated reasoning and multi-step problem solving. The initial release of the Granite 3.0 8B model features support for key agentic capabilities, such as advanced reasoning and a highly-structured chat template and prompting style for implementing tool use workflows. IBM also plans to introduce a new AI agent chat feature to IBM watsonx Orchestrate, which uses agentic capabilities to orchestrate AI Assistants, skills, and automations that help users increase productivity across their teams. IBM plans to continue building agent capabilities across its portfolio in 2025, including pre-built agents for specific domains and use-cases.
Expanded AI-powered delivery platform to supercharge IBM consultants with AI
IBM is also announcing a major expansion of its AI-powered delivery platform, IBM Consulting Advantage. The multi-model platform contains AI agents, applications, and methods like repeatable frameworks that can empower 160,000 IBM consultants to deliver better and faster client value at a lower cost.
As part of the expansion, Granite 3.0 language models will become the default model in Consulting Advantage. Leveraging Granite’s performance and efficiency, IBM Consulting will be able to help maximize the return-on-investment for the generative AI projects of IBM clients.
Another key part of the expansion is the introduction of IBM Consulting Advantage for Cloud Transformation and Management and IBM Consulting Advantage for Business Operations. Each includes domain-specific AI agents, applications, and methods infused with IBM’s best practices so IBM consultants can help accelerate client cloud and AI transformations in tasks, like code modernization and quality engineering, or transform and execute operations across domains, like finance, HR and procurement.
