Back

RAxML-NG 2: Automatic model selection, novel tree search heuristics, and fast branch support metrics

Kozlov, O. M.; Togkousidis, A.; Stelz, C.; Hoehler, D.; Wiegert, J.; Stamatakis, A.

2026-09-11 bioinformatics
10.64898/2026.09.09.750097 bioRxiv
Show abstract

RAxML-NG is a widely used tool for maximum likelihood based phylogenetic inference. In the seven years since the last RAxML-NG publication, we have continuously improved and extended the code. Here, we describe the next major release, RAxML-NG 2.0. It introduces a plethora of new features: integrated model testing, multiple fast branch support metrics, automatic parallelization tuning, phylogenetic difficulty prediction, genotype evolution models, to name but the most important ones. Furthermore, we introduce two novel search heuristics at production code level: the adaptive difficulty-aware heuristic (default) and the fast mode with early-stopping that prevents over-optimization. We perform extensive benchmarking of RAxML-NG 2.0 with respect to its accuracy and speed, and compare it to other popular maximum likelihood based phylogenetic inference tools (IQTree, VeryFastTree) as well as to preceding RAxML-NG versions. In particular, the new fast search heuristic in conjunction with machine learning based branch support prediction induces a 75x inference time reduction compared to RAxML-NG 1.2, with minor to no accuracy loss. The code is available under GNU GPL at https://codeberg.org/amkozlov/raxml-ng.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.