Granite Guardian
IBM's safety and risk-detection model for filtering harmful LLM inputs and outputs
Granite Guardian is IBM’s family of safety models, built to sit alongside a primary LLM and flag risky prompts or responses before they reach a user or an application. It launched with Granite 3.0 in October 2024 in 2B and 8B sizes, both fine-tuned from the base Granite instruct models rather than trained from scratch, and it checks for harms cataloged in IBM’s AI Risk Atlas: things like jailbreak attempts, profanity, social bias, violence, and hallucinated tool calls or retrieval results in agentic workflows. IBM also ships a much smaller 38M-parameter HAP (hate, abuse, profanity) variant for teams that need guardrailing under tighter latency or cost budgets. Granite Guardian is open-weighted under Apache 2.0 and distributed through Hugging Face, Ollama, NVIDIA, and watsonx, and later updates, including a 3.3 release and a 4.1 release with support for user-defined judging criteria, extended the same approach to newer Granite base models.