Enterprise-Specific Performance Matters
IBM released Granite 3.5, the latest generation of its open-source enterprise AI model family, demonstrating performance on sector-specific regulated industry tasks that surpasses comparable-size models from Mistral, Meta, and earlier Granite generations. The models range from 2B to 34B parameters, designed for deployment on enterprise hardware without hyperscaler dependency.
Benchmark Leadership in Regulated Verticals
On the Finance Bench financial reasoning benchmark, Granite 3.5 34B scores 82.3%, compared to Llama 3.3 70B at 74.1% (a larger model). On the MedQA healthcare knowledge benchmark, Granite 3.5 achieves 89.1%. On the LegalBench legal reasoning benchmark, Granite 3.5 34B scores 71.4%, outperforming all open-source models of comparable size.
Why Smaller Can Win on Vertical Tasks
IBM's approach involves training on curated enterprise datasets — IBM's own decades of enterprise data assets — rather than maximizing general-purpose performance. The result is smaller models that outperform larger models on specific enterprise tasks, with lower deployment cost and latency.
Transparency and Trust
All Granite 3.5 models include IBM's AI FactSheets documentation, which details training data sources, known limitations, performance benchmarks, and safety evaluations. IBM offers a legal indemnification program for enterprises using Granite, covering copyright infringement claims arising from model outputs — a differentiator for risk-averse enterprises.
Deployment Options
Granite 3.5 is available on IBM's watsonx platform, Red Hat OpenShift AI, and as open-source weights on Hugging Face. AWS and Azure have announced marketplace availability for Q3 2026.