AlgoTune: Can Language Models Speed Up General-Purpose Numerical Programs?
Paper
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2507.15887
•
Published
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int64 359k
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End of preview. Expand
in Data Studio
How good are language models at coming up with new algorithms? To try to answer this, we built a benchmark, AlgoTune, comprised of 154 widely used math, physics, and computer science functions. For each function, the goal is to write code that produces the same outputs as the original function, while being faster. In addition to the benchmark, we also provide an agent, AlgoTuner, which allows language models to easily optimize code.
AlgoTune can now be easily run on AWS with just an OpenRouter API key and AWS credentials.
Try it out here.
For more information on running AlgoTuner on SLURM or a single machine, please refer to
the code.
Citation
If you found this work helpful, please consider citing it using the following:
AlgoTune citation
@article{press2025algotune, title={AlgoTune: Can Language Models Speed Up General-Purpose Numerical Programs?},
author={Press, Ori and Amos, Brandon and Zhao, Haoyu and Wu, Yikai and Ainsworth, Samuel K. and Krupke, Dominik and Kidger, Patrick and Sajed, Touqir and Stellato, Bartolomeo and Park, Jisun and Bosch, Nathanael and Meril, Eli and Steppi, Albert and Zharmagambetov, Arman and Zhang, Fangzhao and Perez-Pineiro, David and Mercurio, Alberto and Zhan, Ni and Abramovich, Talor and Lieret, Kilian and Zhang, Hanlin and Huang, Shirley and Bethge, Matthias and Press, Ofir},
journal={arXiv preprint arXiv:2507.15887},
year={2025},
doi={10.48550/arXiv.2507.15887},
url={https://arxiv.org/abs/2507.15887}}
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