This release introduces an evaluation function based on a NNUE-style architecture of input size 728, with 8 buckets of 256 hidden neurons which is chosen depending on the number of pieces left on the board. This network was trained on 125 million positions from self-play games using Weiawaga v4.0. The only new search change is the introduction of reverse futility pruning. The release also includes many minor optimizations, and is ~350 Elo stronger than Weiawaga v4.0.