@inproceedings{li-etal-2026-llmrouterbench,
    title = "{LLMR}outer{B}ench: A Massive Benchmark and Unified Framework for {LLM} Routing",
    author = "Li, Hao  and
      Zhang, Yiqun  and
      Guo, Zhaoyan  and
      Wang, Chenxu  and
      Tang, Shengji  and
      Zhang, Qiaosheng  and
      Chen, Yang  and
      Qi, Biqing  and
      Ye, Peng  and
      Bai, Lei  and
      Wang, Zhen  and
      Hu, Shuyue",
    editor = "Liakata, Maria  and
      Moreira, Viviane P.  and
      Zhang, Jiajun  and
      Jurgens, David",
    booktitle = "Findings of the {A}ssociation for {C}omputational {L}inguistics: {ACL} 2026",
    month = jul,
    year = "2026",
    address = "San Diego, California, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl/2026.findings-acl.1881/",
    pages = "37733--37754",
    ISBN = "979-8-89176-395-1",
    abstract = "Large language model (LLM) routing assigns each query to the most suitable model from an ensemble. We introduce LLMRouterBench, a large-scale benchmark and unified framework for LLM routing. It comprises over 400K instances from 21 datasets and 33 models. Moreover, it provides comprehensive metrics for both performance-oriented and performance-cost trade-off routing, and integrates 10 representative routing baselines. Using LLMRouterBench, we systematically re-evaluate the field. While confirming strong model complementarity{---}the central premise of LLM routing{---}we find that many routing methods exhibit similar performance under unified evaluation, and several recent approaches, including commercial routers, fail to reliably outperform a simple baseline. Meanwhile, a substantial gap remains to the Oracle, driven primarily by persistent model-recall failures. We further show that backbone embedding models have limited impact, that larger ensembles exhibit diminishing returns compared to careful model curation, and that the benchmark also enables latency-aware analysis. All code and data are available at https://github.com/ynulihao/LLMRouterBench."
}