Hello lovely people,
I would like to announce LogitNash.jl – a solver for finite multiplayer general-sum games, with the slightly provocative claim of finding a mixed Nash Equilibrium more than 100x faster than the state of the art (under fair and comprehensive benchmarks).
The iterative solver is based on the convergent theory of Turocy (2005), but optimized for speed and re-parametrized for better solution accuracy.
The algorithm is optimized for large dense games and solves a 4-player 66-action Blotto game (same as considered by ADIDAS, 290 MB encoded as F32) in around 12 seconds (on a ThinkPad Gen 2) to a relative maximal deviation incentive of less than 10^{-6}.
If you don’t believe me (and I hope You don’t), checkout the detailed benchmarks or try it yourself using the published scripts for Bash and SLURM.
If you have suggestions for improvements or comparisons you would like to see, please get in touch.
P.S. If any of You experienced solver maintainers have tips and or lessons-learned for the final stable API, I would love to hear from you! 
P.P.S. This is my first package, sorry if this isn’t how packages are meant to be announced.