Most physics-informed neural networks are far too big
Research PINNs are routinely tens to hundreds of times bigger than the problem needs. Burgers’ equation plateaus at about 150 parameters, and a hyperelasticity model I saw used 424x more than necessary. Start small and scale only when the physics loss will not converge.