> For the complete documentation index, see [llms.txt](https://docs.bespokelabs.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.bespokelabs.ai/models/bespoke-minicheck.md).

# Bespoke MiniCheck

> *“Hallucination-free answers demand verifiable grounding.  Bespoke-MiniCheck makes that easy.”*

#### What is grounded factuality?

Grounded factuality (a.k.a. textual entailment) measures whether a *claim* is supported, refuted, or not verifiable given an explicit *context* document.  The metric is critical for Retrieval-Augmented Generation (RAG): if a claim is not grounded in the retrieved context, the model has hallucinated.

#### Why Bespoke-MiniCheck?

* Best-in-class accuracy – Tops the public **LLM-AggreFact** leaderboard at 77.4 %, surpassing models that are many times larger.
* Fast – \~200 ms end-to-end latency on a single modern GPU; < 100 ms with optional optimisations.
* Lightweight – Runs comfortably on consumer laptops (MacBook-class hardware).
* Easy to integrate – Drop-in HuggingFace model with a single probability output: *support score*.