mlp                         0.1239962 -> 0.0213232  error 1.25e-11
cnn                         0.2692596 -> 0.2325899  error 1.84e-11
resnet                      0.2904074 -> 0.2322504  error 2.47e-12
rnn                         0.0858071 -> 0.0695565  error 2.18e-12
gru                         0.0596449 -> 0.0565293  error 2.21e-11
lstm                        0.0879157 -> 0.0683431  error 1.00e-11
decoder-transformer         1.0777150 -> 1.0268303  error 1.42e-11
encoder-transformer         1.2418545 -> 0.4833821  error 1.16e-11
encoder-decoder-transformer 0.7702176 -> 0.7322609  error 1.22e-11
vit                         0.8795806 -> 0.2972389  error 1.42e-11
gnn                         0.2987850 -> 0.2895769  error 6.34e-12
selective-ssm               0.2437729 -> 0.2435133  error 2.04e-12
delta-attention-hybrid      0.4346769 -> 0.1398037  error 2.72e-10
soft-moe                    0.2481291 -> 0.1628168  error 3.45e-12
sparse-moe-fixed-routes     0.2513659 -> 0.1724777  error 3.05e-12
diffusion-unet              0.2563024 -> 0.2374049  error 4.16e-12
diffusion-transformer       0.2982492 -> 0.1961924  error 1.95e-10
vae                         0.9860251 -> 0.3802710  error 1.82e-11
gan-generator               0.4330408 -> 0.4329290  error 2.64e-12
gan-discriminator           0.7385610 -> 0.7151317  error 6.14e-12
realnvp                     0.3146167 -> -0.0115711  error 3.37e-11
flow-matching               0.8040606 -> 0.6987641  error 1.14e-11
clip                        1.2949897 -> 0.4550934  error 6.62e-10
conformer                   0.3459806 -> 0.0682097  error 5.42e-12
dlrm                        0.6663279 -> 0.6584869  error 5.54e-12
higher-order                0.3765333 -> 0.0000001  error 5.50e-13
