A from-scratch transformer scored 44% on ARC-AGI-1 for 67 cents of total lifetime compute.

1.5 hours on a single 5090, 44% on ARC-AGI-1 and 7% on ARC-2, 67 cents covering training and inference (mvakde). The method converts puzzle pairs to token sequences, trains autoregressively on evaluation inputs with labels hidden, uses per-task additive embeddings with 3D RoPE and color/dihedral augmentation, then takes the two most common outputs. Every upgrade over the author's previous attempt is a commodity part: SwiGLU, RMSNorm, eight layers instead of four, NorMuon instead of AdamW. Author reports matching TRM and HRM while beating many LLMs.