From Global Benchmarks to Local Evaluations: Benchmarking LLMs for the German Public Sector
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Abstract (arXiv)
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 M"OVE, 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.
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References · 12
- 2020Measuring Massive Multitask Language Understandingcited by 7,963
- 2019SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systemscited by 1,729
- 2019Energy and Policy Considerations for Deep Learning in NLPcited by 1,254
- 2024Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluationcited by 191
- 2024Political Compass or Spinning Arrow? Towards More Meaningful Evaluations for Values and Opinions in Large Language Modelscited by 162
- 2024BetterBench: Assessing AI Benchmarks, Uncovering Issues, and Establishing Best Practicescited by 114
- 2022EUR-Lex-Sum: A Multi- and Cross-lingual Dataset for Long-form Summarization in the Legal Domaincited by 40
- 2021GermanQuAD and GermanDPR: Improving Non-English Question Answering and Passage Retrievalcited by 39
- 2025SEA-HELM: Southeast Asian Holistic Evaluation of Language Modelscited by 19
- 2025Unveiling Environmental Impacts of Large Language Model Serving: A Functional Unit Viewcited by 11
- 2026The CitizenQuery Benchmark: A Novel Dataset and Evaluation Pipeline for Measuring LLM Performance in Citizen Query Taskscited by 5
- 2026M"OVE: A Holistic LLM Benchmark for the German Public Sectorcited by 1
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