From Global Benchmarks to Local Evaluations: Benchmarking LLMs for the German Public Sector

Abstract:Public institutions face a persistent challenge in selecting LLMs suited to their specific context. Existing benchmarks, however, are of limited use as they primarily reflect English-language and US-centric settings, and often only evaluate task performance. In this paper, we present first results of MÖVE, a holistic evaluation framework for the German public sector, examining three rarely considered governance dimensions: energy consumption, provider transparency, and knowledge of German-party positions. Our results reveal significant trade-offs, with no single model excelling across all dimensions: estimated energy consumption varies more than 60-fold and is not explained by model size alone, information disclosure varies systematically across providers, and European models do not exhibit stronger knowledge of German party positions. Model selection for public institutions thus cannot rely on performance rankings alone. Instead, evaluations should also reflect the governance requirements of the deployment context.

Computation and Language (cs.CL)

arXiv:2608.17827 [cs.CL]

(or arXiv:2608.17827v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2608.17827 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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