- Granite 3.2 – small AI models offering reasoning, vision,
and guardrail capabilities with a developer friendly
license
- Updated Granite time series models that offer long-range
forecasting with less than 10M
parameters
ARMONK,
N.Y., Feb. 26, 2025 /PRNewswire/ -- IBM (NYSE:
IBM) today debuted the next generation of its Granite large
language model (LLM) family, Granite 3.2, in a continued effort to
deliver small, efficient, practical enterprise AI for real-world
impact.
All Granite 3.2 models are available under the permissive Apache
2.0 license on Hugging Face. Select models are available today on
IBM watsonx.ai, Ollama, Replicate, and LM Studio, and expected
soon in RHEL AI 1.5 – bringing advanced capabilities to businesses
and the open-source community. Highlights include:
- A new vision language model (VLM) for document
understanding tasks which demonstrates performance that matches or
exceeds that of significantly larger models – Llama 3.2
11B and Pixtral 12B – on the essential enterprise benchmarks
DocVQA, ChartQA, AI2D and OCRBench1. In addition to
robust training data, IBM used its own open-source Docling
toolkit to process 85 million PDFs and generated 26 million
synthetic question-answer pairs to enhance the VLM's ability to
handle complex document-heavy workflows.
- Chain of thought capabilities for enhanced reasoning in
the 3.2 2B and 8B models, with the ability to switch
reasoning on or off to help optimize efficiency. With this
capability, the 8B model
achieves double-digit improvements from its predecessor in
instruction-following benchmarks like ArenaHard and Alpaca Eval
without degradation of safety or performance elsewhere2.
Furthermore, with the use of novel inference scaling methods,
the Granite 3.2 8B model can be
calibrated to rival the performance of much larger models like
Claude 3.5 Sonnet or GPT-4o on math reasoning benchmarks such as
AIME2024 and MATH500.3
- Slimmed-down size options for Granite Guardian safety
models that maintain performance of previous Granite 3.1 Guardian
models at 30% reduction in size. The 3.2 models also introduce a
new feature called verbalized confidence, which offers more nuanced
risk assessment that acknowledges ambiguity in safety
monitoring.
IBM's strategy to deliver smaller, specialized AI models for
enterprises continues to demonstrate efficacy in testing, with the
Granite 3.1 8B model recently
yielding high marks on accuracy in the Salesforce LLM Benchmark for
CRM.
The Granite model family is supported by a robust ecosystem of
partners, including leading software companies embedding the LLMs
into their technologies.
"At CrushBank, we've seen first-hand how IBM's open, efficient
AI models deliver real value for enterprise AI – offering the right
balance of performance, cost-effectiveness, and scalability," said
David Tan, CTO, CrushBank. "Granite
3.2 takes it further with new reasoning capabilities, and we're
excited to explore them in building new agentic
solutions."
Granite 3.2 is an important step in the evolution of IBM's
portfolio and strategy to deliver small, practical AI for
enterprises. While chain of thought approaches for reasoning are
powerful, they require substantial compute power that is not
necessary for every task. That is why IBM has introduced the
ability to turn chain of thought on or off programmatically. For
simpler tasks, the model can operate without reasoning to reduce
unnecessary compute overhead. Additionally, other reasoning
techniques like inference scaling have shown that the Granite 3.2
8B model can match or exceed the
performance of much larger models on standard math reasoning
benchmarks. Evolving methods like inference scaling remains a key
area of focus for IBM's research teams.4
Alongside Granite 3.2 instruct, vision, and guardrail models,
IBM is releasing the next generation of its TinyTimeMixers (TTM)
models (sub 10M parameters), with
capabilities for longer-term forecasting up to two years into the
future. These make for powerful tools in long-term trend analysis,
including finance and economics trends, supply chain demand
forecasting and seasonal inventory planning in retail.
"The next era of AI is about efficiency, integration, and
real-world impact – where enterprises can achieve powerful outcomes
without excessive spend on compute," said Sriram Raghavan, VP, IBM AI Research. "IBM's
latest Granite developments focus on open solutions demonstrate
another step forward in making AI more accessible, cost-effective,
and valuable for modern enterprises."
To learn more about Granite 3.2, read this technical
article.
About IBM
IBM is a leading provider of global hybrid cloud and AI, and
consulting expertise. We help clients in more than 175 countries
capitalize on insights from their data, streamline business
processes, reduce costs, and gain a competitive edge in their
industries. Thousands of governments and corporate entities in
critical infrastructure areas such as financial services,
telecommunications and healthcare rely on IBM's hybrid cloud
platform and Red Hat OpenShift to affect their digital
transformations quickly, efficiently, and securely. IBM's
breakthrough innovations in AI, quantum computing,
industry-specific cloud solutions and consulting deliver open and
flexible options to our clients. All of this is backed by IBM's
long-standing commitment to trust, transparency, responsibility,
inclusivity, and service. Visit www.ibm.com
for more information.
Media
contact:
Amy Angelini
IBM AI
Communications
alangeli@us.ibm.com
1
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Vision model benchmark
results are available in IBM's technical article, IBM Granite
3.2: Reasoning, Vision, Forecasting, and More, published
February 26, 2025.
|
2
|
Instruct model
benchmark results are available in IBM's technical article, IBM
Granite 3.2: Reasoning, Vision, Forecasting, and More,
published February 26, 2025.
|
3
|
Inference scaling
benchmark results are available in IBM's technical research blog,
Reasoning in Granite 3.2 Using Inference Scaling,
published February 26, 2025.
|
4
|
Reasoning in Granite
3.2 Using Inference Scaling, IBM, published
February 26, 2025.
|
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SOURCE IBM