TritonDFT: An Agentic Framework and Benchmark for Automated DFT Workflows

Density Functional Theory (DFT) is a cornerstone of materials science, yet executing DFT in practice requires coordinating a complex, multi-step workflow. Existing tools and LLM-based solutions automate parts of the steps, but lack support for full workflow automation, diverse task adaptation, and accuracy–cost trade-off optimization in DFT parameter choices. To this end, we present TritonDFT, an agentic framework adopting an expert-curated, extensible workflow design, with Pareto-aware parameter inference and automated parallelization, to enable efficient and accurate DFT execution. We further introduce DFTBench, a benchmark for evaluating the agent's multi-dimensional capabilities, spanning accuracy-cost trade-off optimization, high-performance computing knowledge, and monetary cost efficiency. Our code and benchmark suite can be found at https://anonymous.4open.science/r/TritonDFT-43C7/.