What is Granite Guardian 3.0 2B?
Granite Guardian 3.0 2B is an IBM Research safety and evaluation model built from Granite 3.0 2B Instruct. It is not intended to be a general conversational assistant. Instead, it acts as a guardrail: an application supplies a prompt, a model response, or retrieval context, and Granite Guardian evaluates that material against a selected risk category.
The model’s usual output is a yes-or-no safety judgment, rather than a long explanation or an unrestricted generated answer. This makes it a practical component in systems that need to decide whether to block content, request a rewrite, route a case for review, or allow a response to continue to the user.
IBM released the model on October 21, 2024 as an open-weight model under the Apache 2.0 license. The official model card identifies Granite Guardian 3.1 2B as a newer version, so Granite Guardian 3.0 2B is best understood as an earlier member of IBM’s Granite Guardian line rather than the newest release in that family.
What the model can detect
Granite Guardian 3.0 2B includes built-in risk categories for both ordinary content safety and retrieval-augmented generation, or RAG, evaluation. RAG systems provide a language model with retrieved documents or passages before it generates an answer. The retrieved material can be relevant, incomplete, or misleading, so a separate evaluator can help identify problems before an answer reaches the user.
- General harm: potentially harmful user prompts or model responses.
- Jailbreaking: attempts to bypass an application’s safety instructions or restrictions.
- Social bias: problematic or discriminatory content involving social groups.
- Violence, profanity, and sexual content: specific classes of unsafe or unsuitable material.
- Unethical behavior: content associated with unethical requests or actions.
- Context relevance: whether retrieved context is relevant to the question.
- Groundedness: whether an answer is supported by the supplied context rather than making unsupported claims.
- Answer relevance: whether the response addresses the user’s question.
The model card reports an average area under the curve (AUC) of 0.81 across the listed TRUE RAG hallucination benchmarks. This is a provider-reported research result for the evaluated benchmarks, not a guarantee of accuracy on every application’s data or safety policy.
Position in IBM’s model lineup
Granite Guardian 3.0 2B belongs to IBM’s Granite family but has a different role from a normal instruction-following language model. Granite 3.0 2B Instruct is the base model from which it was fine-tuned; Granite Guardian adds safety and RAG-risk classification behavior rather than focusing on general chat, broad knowledge work, or code generation.
The model is also distinct from a hosted moderation API in an important practical way: the supplied research describes it as downloadable and runnable with local or self-hosted inference tools. Supported options mentioned in the model materials include Transformers, vLLM, SGLang, Docker Model Runner, Ollama, and LM Studio. The exact deployment method, hardware requirement, and operating cost depend on the selected runtime and infrastructure.
Because Granite Guardian 3.1 2B is identified as a newer version, users starting a new evaluation should compare that successor before standardizing on 3.0 2B. Granite Guardian 3.0 2B can still be relevant when compatibility with an existing deployment, model artifact, or evaluation workflow matters.
Technical specifications and supported modalities
| Specification | Granite Guardian 3.0 2B |
|---|---|
| Provider | IBM |
| Model type | Safety model |
| Release date | October 21, 2024 |
| License | Apache 2.0 |
| Context length | 8,192 tokens |
| Input | Text |
| Output | Text safety judgments |
| Image, audio, and video input | Not supported |
| Direct image, audio, or video output | Not supported |
| Tool or function use | Not supported |
| Maximum output tokens | Not specified in the supplied research |
The 8,192-token context length limits the total text the model can process in a request. Applications that combine a long user prompt, retrieved passages, and a candidate answer should keep the complete evaluation input within that limit. The supplied information does not specify a separate maximum number of output tokens.
Granite Guardian 3.0 2B is English-only according to the supplied model notes. It should therefore not be treated as a multilingual safety classifier without separate validation. Its text-only design also rules out direct evaluation of image, audio, or video content unless another system first converts that material into text.
Main strengths and trade-offs
The model’s strongest distinction is specialization. A compact safety model can be placed after a generative model to inspect its answer, or before generation to screen a user request. Its risk categories also extend beyond conventional harmful-content moderation: context relevance, groundedness, and answer relevance make it useful for checking RAG workflows.
Its open-weight Apache 2.0 distribution is another practical advantage for organizations that need local execution, deployment control, or integration with existing inference infrastructure. The model can be run through several local and self-hosted tools rather than requiring a separately priced hosted endpoint. There is no provider-hosted input or output price supplied for this model, so a precise per-token cost cannot be stated. Local deployment still has infrastructure and operational costs.
Its limitations follow from the same specialization. Granite Guardian 3.0 2B is not a replacement for a general-purpose assistant, a web-search system, a code-generation model, or a multimodal content understanding model. The supplied editorial assessment gives it a reasoning score of 2 out of 10 and a coding score of 1 out of 10, but these are editorial relative scores for a specialized safety model, not IBM-published benchmark ratings. The same assessment rates speed at 7 out of 10 and cost at 8 out of 10; these are also subjective estimates rather than guaranteed performance or pricing figures.
Good use cases
- Prompt screening: evaluate user requests for harmful, abusive, unsafe, or jailbreak-related content before passing them to a generative model.
- Response moderation: inspect a draft answer before displaying it to a user or storing it in an application.
- RAG quality checks: assess whether retrieved context is relevant and whether an answer is grounded in that context.
- Local safety pipelines: deploy a guardrail inside a controlled environment where sending prompts and responses to an external moderation service is undesirable.
- Layered evaluation: combine its yes-or-no judgments with application-specific rules, human review, or a larger evaluator for difficult cases.
For example, a customer-support system could send the user’s question and the proposed answer to Granite Guardian. The application could then use the returned safety category to block a harmful request, reject an answer that is not grounded in the retrieved help-center text, or flag an ambiguous result for human review.
When to choose this model
Choose Granite Guardian 3.0 2B when the primary requirement is a compact, self-hostable text safety or RAG-evaluation component rather than conversation quality. It is particularly suitable when Apache 2.0 licensing, local inference, and a defined set of safety judgments are more important than open-ended reasoning or generation.
A larger general-purpose model is more appropriate when the system must write detailed responses, solve complex problems, generate production code, or handle broad knowledge tasks. A multimodal safety system is a better choice when the inputs include images, audio, or video. A multilingual alternative should be evaluated for applications serving languages beyond English.
Users choosing between Granite Guardian 3.0 2B and a newer safety model should compare category coverage, language support, evaluation results, runtime compatibility, and policy behavior. In particular, IBM’s stated newer Granite Guardian 3.1 2B deserves consideration for new projects, while 3.0 2B may remain useful for established deployments that depend on its existing behavior or packaging.
Pricing and availability
Granite Guardian 3.0 2B is described as an open-weight model available for download under the Apache 2.0 license. The supplied research does not provide a hosted API price, subscription fee, input-token price, or output-token price. Consequently, there is no verified recurring model price to report.
Running the model locally or on a private server is not free in an operational sense: users must provide suitable compute, storage, monitoring, and maintenance. Those costs vary by deployment and are separate from any license fee. The model is available through the IBM Granite model card and associated repositories and can be used with the local inference tools identified in the supplied research.
Bottom line
Granite Guardian 3.0 2B is best viewed as a focused safety component, not a smaller general-purpose chatbot. Its value comes from screening prompts and responses and from checking several RAG failure modes, including irrelevant context, ungrounded answers, and irrelevant responses. The 8,192-token text context, English-only scope, lack of multimodal support, and absence of tool use define its boundaries. For local moderation and RAG guardrails where open weights and deployment control matter, it is a practical option; for generation, coding, multilingual work, or multimodal moderation, another type of model is more appropriate.