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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Kato2026Sil-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	alexnet_training_seed_07	.973
2	eva02_large_in22k	.941
3	convnext_base_fb_in22k_ft_in1k	.915
4	vit_huge_clip336_laion	.913
5	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.910
6	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.906
7	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.878
8	resnext101_32x32d_wsl	.850
9	dinov2_vitg14_lc	.820
10	dinov2_vitl14_reg_lc	.800
11	dinov2_vitg14_reg_lc	.798
12	convnext_large_clip_laion2b_finelayers	.798
13	convnext_large_in22k_supervised	.789
14	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.776
15	convnext_xxlarge_clip	.771
16	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.769
17	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.766
18	vit_large_patch14_clip_224:laion2b_ft_in1k	.748
19	vit_large_patch14_clip_224:openai_ft_in1k	.746
20	convnext_large:fb_in22k_ft_in1k	.746
21	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.739
22	vit_large_clip336_openai	.728
23	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.727
24	resnext101_32x48d_wsl	.716
25	AdvProp_efficientnet-b6	.712
26	resnext101_32x8d_wsl	.689
27	AdvProp_efficientnet-b4	.672
28	convnext_base:clip_laiona_augreg_ft_in1k_384	.649
29	deit3_base_patch16_224_fb_in22k_ft_in1k	.645
30	resnext101_32x16d_wsl	.642
31	vit_large_patch14_clip_336:laion2b_ft_in1k	.642
32	ViT_L_32_imagenet1k	.639
33	dinov2_vitl14_lc_res336	.635
34	dinov2_vitl14_lc	.627
35	AdvProp_efficientnet-b2	.626
36	AT_efficientnet-b2	.626
37	AdvProp_efficientnet-b7	.624
38	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.614
39	deit3_base_patch16_224_fb_in1k	.596
40	convnext_base_fb_in1k	.595
41	convnext_xlarge:fb_in22k_ft_in1k	.593
42	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.590
43	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.549
44	convnext_tiny:in12k_ft_in1k	.542
45	focalnet_tiny_lrf_in1k	.535
46	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.533
47	vit_relpos_base_patch16_clsgap_224:sw_in1k	.532
48	AdvProp_efficientnet-b8	.525
49	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.512
50	voneresnet-50-robust	.506
51	convnext_tiny_imagenet_full_seed-0	.504
52	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.500
53	convnext_large_imagenet_full_seed-0	.497
54	resnet50_robust_l2_eps1	.493
55	resnet_101_v2	.492
56	seresnext50_32x4d	.492
57	vit_base_patch16_clip_224:openai_ft_in1k	.487
58	convnext_base_imagenet_full_seed-0	.471
59	regnety_032	.462
60	cv_18_dagger_408_pretrained	.461
61	convnext_small_imagenet_full_seed-0	.459
62	resnet50_robust_l2_eps3	.452
63	imagenet_l2_3_0	.452
64	resnet-50-robust	.452
65	antialias-resnet152	.427
66	resnet50_st_wzc_2	.426
67	convnext_base_fb_in1k_gram_aligned_dinov3	.413
68	deit_base_imagenet_full_seed-0	.408
69	convnext_tiny_sup	.408
70	deit_large_imagenet_full_seed-0	.405
71	pnasnet_large_halfPrecision	.400
72	mehrer2020_alexnet_training_seed_01_fov12	.390
73	mehrer2020_alexnet_training_seed_01_fov16	.387
74	deit_small_imagenet_full_seed-0	.385
75	blt_vs	.383
76	resnet50_ewconplus_wzc_seed2_2__323	.374
77	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.373
78	effnetb1_272x240	.372
79	resnet50_hvs_wzc	.368
80	resnet101_imagenet_full	.368
81	resnet50_st_wzc_seed6_2_323	.365
82	resnet_101_v1	.365
83	resnet50_st_wzc_seed3_2_323	.364
84	resnet50_ewconplus_wzc	.361
85	resnet_SIN_IN_FT_IN	.360
86	resnet50-SIN_IN_IN	.360
87	inception_v3	.358
88	resnet152_imagenet_full	.356
89	grcnn_109	.349
90	vonegrcnn_47e	.345
91	resnet50_st_wzc_seed7_2_323	.344
92	custom_model_cv_18_dagger_408	.342
93	densenet-201	.341
94	resnet50_ewconplus_wzc_seed5_2__323	.340
95	resnet50_ewconplus_wzc_seed6_2_323	.340
96	Res2Net50_26w_4s	.338
97	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.337
98	cvt_cvt-21-384-in1k_4_LucyV4	.334
99	efficientnet_b0	.324
100	vonegrcnn_62e_nobn	.319
101	resnet_50_v1	.319
102	resnet50_tutorial	.319
103	resnet50-sup	.319
104	cvt_cvt-13-224-in1k_4_LucyV4	.319
105	voneresnet-50	.314
106	resnet50-SIN_IN	.313
107	nasnet_mobile	.311
108	resnet_50_v1_spiking	.311
109	voneresnet-50-non_stochastic	.308
110	resnet_50_v2	.305
111	densenet-121	.303
112	resnet_152_v2	.301
113	antialiased-r50	.291
114	cvt_cvt-21-224-in1k_4_LucyV4	.285
115	resnet34_imagenet_full	.285
116	efficientnet_b1_imagenet_full	.280
117	mehrer2020_alexnet_training_seed_04	.277
118	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.274
119	grcnn	.273
120	efficientnet_b0_imagenet_full	.271
121	mehrer2020_alexnet_training_seed_01	.269
122	cvt_cvt-13-384-in1k_4_LucyV4	.266
123	resnet50-SIN	.264
124	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.263
125	mehrer2020_alexnet_training_seed_02	.253
126	AlexNet_SIN	.245
127	efficientnet_b2_imagenet_full	.239
128	resnet50-moclr8deg	.239
129	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.236
130	mehrer2020_alexnet_training_seed_03	.235
131	convnext_small_imagenet_100_seed-0	.235
132	resnet50_byol_linhead	.232
133	shufflenet_v2_x1_0	.231
134	resnet50_imagenet_full	.230
135	ReAlnet10	.225
136	ReAlnet08	.224
137	resnet18_imagenet_full	.224
138	resnet50_barlowtwins_linhead	.215
139	ReAlnet07	.207
140	resnet_50_v1_spiking_l4a	.205
141	ijepa_vith14_linhead	.205
142	ReAlnet09	.204
143	mehrer2020_alexnet_training_seed_05	.203
144	ReAlnet04	.198
145	resnet50_simsiam_linhead	.198
146	AlexNet_SIN_fov12	.197
147	mobilenet_v2_1_4_224	.193
148	resnet50_vicreg_linhead	.192
149	convnext_femto_ols:d1_in1k	.190
150	AlexNet_SIN_fov16	.189
151	eicircuit_resnet18_bn_20260919	.180
152	vgg_16	.174
153	resnet50-vitoimagevidnet8	.174
154	resnet50-VITO-8deg-cc	.174
155	resnet50_simclr_linhead_01norm	.170
156	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.156
157	alexnet	.129
158	mehrer2020_alexnet_training_seed_01_fov4	.000
159	mobilenet_v2_1_0_128
160	gabor_filter_entropy_4x4_v2_forcedCosine
161	gabor_filter_entropy_4x4_v2
162	dinov2_vitl14_reg_lc_featread
163	deepeisnn_ei_imagenet_resnet18
164	alexnet_training_seed_01
165	alexnet_training_seed_10
166	alexnet_training_seed_09
167	alexnet_training_seed_06
168	alexnet_training_seed_03
169	alexnet_training_seed_02
170	hmax
171	ReAlnet01_cornet
172	compact_resnet50_robust_V4
173	VOneCORnet-S
174	ReAlnet03_cornet
175	ReAlnet04_cornet
176	ReAlnet01_cornet_fov4

Benchmark bibtex

None

Ceiling

0.52.

Note that scores are relative to this ceiling.

Data: Kato2026Sil

Metric: error_consistency