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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Kato2026Fil-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.897
2	blt_vs	.835
3	AdvProp_efficientnet-b8	.824
4	ViT_L_32_imagenet1k	.818
5	AT_efficientnet-b2	.793
6	AdvProp_efficientnet-b2	.793
7	resnet50-SIN	.771
8	effnetb1_272x240	.763
9	resnet_101_v1	.755
10	cv_18_dagger_408_pretrained	.748
11	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.748
12	AdvProp_efficientnet-b4	.741
13	inception_v3	.736
14	resnext101_32x8d_wsl	.720
15	vonegrcnn_62e_nobn	.693
16	deit3_base_patch16_224_fb_in22k_ft_in1k	.692
17	AdvProp_efficientnet-b7	.674
18	resnet50-moclr8deg	.664
19	vgg_16	.661
20	resnet152_imagenet_full	.660
21	pnasnet_large_halfPrecision	.643
22	resnet18_imagenet_full	.640
23	efficientnet_b2_imagenet_full	.638
24	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.638
25	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.632
26	voneresnet-50-robust	.632
27	mehrer2020_alexnet_training_seed_02	.625
28	regnety_032	.624
29	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.622
30	resnet50_robust_l2_eps1	.620
31	resnet50_simsiam_linhead	.617
32	cvt_cvt-13-384-in1k_4_LucyV4	.616
33	vit_large_patch14_clip_224:laion2b_ft_in1k	.610
34	vonegrcnn_47e	.609
35	nasnet_mobile	.604
36	vit_base_patch16_clip_224:openai_ft_in1k	.597
37	vit_relpos_base_patch16_clsgap_224:sw_in1k	.596
38	seresnext50_32x4d	.590
39	resnet_152_v2	.588
40	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.588
41	Res2Net50_26w_4s	.585
42	convnext_tiny_sup	.585
43	resnet_50_v2	.584
44	shufflenet_v2_x1_0	.582
45	antialias-resnet152	.580
46	resnet50_byol_linhead	.579
47	resnet50_ewconplus_wzc_seed5_2__323	.578
48	ijepa_vith14_linhead	.577
49	deit_large_imagenet_full_seed-0	.577
50	cvt_cvt-21-224-in1k_4_LucyV4	.576
51	convnext_tiny_imagenet_full_seed-0	.576
52	vit_large_patch14_clip_336:laion2b_ft_in1k	.575
53	resnet50-SIN_IN	.568
54	focalnet_tiny_lrf_in1k	.568
55	convnext_small_imagenet_full_seed-0	.567
56	deit_small_imagenet_full_seed-0	.567
57	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.562
58	resnet50-vitoimagevidnet8	.561
59	resnet50-VITO-8deg-cc	.561
60	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.561
61	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.560
62	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.557
63	resnet50_ewconplus_wzc_seed2_2__323	.557
64	cvt_cvt-13-224-in1k_4_LucyV4	.555
65	AdvProp_efficientnet-b6	.555
66	resnet50_robust_l2_eps3	.554
67	imagenet_l2_3_0	.554
68	resnet-50-robust	.554
69	resnet50_simclr_linhead_01norm	.552
70	deit3_base_patch16_224_fb_in1k	.550
71	convnext_femto_ols:d1_in1k	.548
72	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.547
73	voneresnet-50-non_stochastic	.543
74	custom_model_cv_18_dagger_408	.539
75	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.536
76	efficientnet_b1_imagenet_full	.535
77	ReAlnet09	.534
78	resnet50_ewconplus_wzc	.528
79	resnet50_st_wzc_seed7_2_323	.528
80	convnext_base_imagenet_full_seed-0	.525
81	resnet50_ewconplus_wzc_seed6_2_323	.524
82	cvt_cvt-21-384-in1k_4_LucyV4	.519
83	resnet_50_v1_spiking	.517
84	efficientnet_b0_imagenet_full	.514
85	voneresnet-50	.512
86	vit_large_clip336_openai	.510
87	vit_large_patch14_clip_224:openai_ft_in1k	.502
88	resnet34_imagenet_full	.501
89	resnet50_imagenet_full	.501
90	resnet50_barlowtwins_linhead	.501
91	resnet50_st_wzc_seed3_2_323	.497
92	efficientnet_b0	.490
93	mehrer2020_alexnet_training_seed_04	.490
94	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.489
95	densenet-121	.489
96	resnet50_st_wzc_seed6_2_323	.488
97	resnet50-SIN_IN_IN	.484
98	resnet_SIN_IN_FT_IN	.484
99	resnext101_32x16d_wsl	.483
100	convnext_base_fb_in22k_ft_in1k	.478
101	resnet101_imagenet_full	.475
102	antialiased-r50	.473
103	mehrer2020_alexnet_training_seed_05	.472
104	resnet50_st_wzc_2	.464
105	resnet50_vicreg_linhead	.457
106	convnext_xlarge:fb_in22k_ft_in1k	.446
107	alexnet	.444
108	mobilenet_v2_1_4_224	.439
109	resnet50_hvs_wzc	.437
110	resnet_101_v2	.436
111	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.435
112	convnext_base_fb_in1k_gram_aligned_dinov3	.423
113	grcnn_109	.420
114	resnet_50_v1	.418
115	resnet50_tutorial	.418
116	resnet50-sup	.418
117	densenet-201	.417
118	grcnn	.415
119	ReAlnet04	.414
120	ReAlnet08	.411
121	mehrer2020_alexnet_training_seed_01_fov12	.405
122	deit_base_imagenet_full_seed-0	.399
123	mehrer2020_alexnet_training_seed_03	.396
124	mehrer2020_alexnet_training_seed_01	.396
125	convnext_small_imagenet_100_seed-0	.396
126	eicircuit_resnet18_bn_20260919	.394
127	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.394
128	convnext_base:clip_laiona_augreg_ft_in1k_384	.392
129	resnext101_32x48d_wsl	.375
130	mehrer2020_alexnet_training_seed_01_fov16	.369
131	resnet_50_v1_spiking_l4a	.363
132	convnext_large_imagenet_full_seed-0	.359
133	ReAlnet07	.352
134	vit_huge_clip336_laion	.339
135	resnext101_32x32d_wsl	.332
136	convnext_large_clip_laion2b_finelayers	.323
137	AlexNet_SIN_fov12	.323
138	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.321
139	convnext_base_fb_in1k	.321
140	ReAlnet10	.312
141	convnext_xxlarge_clip	.311
142	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.306
143	AlexNet_SIN_fov16	.288
144	convnext_tiny:in12k_ft_in1k	.287
145	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.267
146	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.250
147	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.232
148	convnext_large_in22k_supervised	.210
149	AlexNet_SIN	.198
150	dinov2_vitg14_lc	.188
151	dinov2_vitg14_reg_lc	.186
152	convnext_large:fb_in22k_ft_in1k	.134
153	eva02_large_in22k	.133
154	dinov2_vitl14_reg_lc	.106
155	mehrer2020_alexnet_training_seed_01_fov4	.086
156	dinov2_vitl14_lc	.070
157	dinov2_vitl14_lc_res336	.058
158	alexnet_training_seed_09	.000
159	alexnet_training_seed_07	.000
160	alexnet_training_seed_03	.000
161	mobilenet_v2_1_0_128
162	gabor_filter_entropy_4x4_v2_forcedCosine
163	gabor_filter_entropy_4x4_v2
164	dinov2_vitl14_reg_lc_featread
165	deepeisnn_ei_imagenet_resnet18
166	alexnet_training_seed_01
167	alexnet_training_seed_10
168	alexnet_training_seed_06
169	alexnet_training_seed_02
170	hmax
171	ReAlnet01_cornet_fov4
172	ReAlnet01_cornet
173	compact_resnet50_robust_V4
174	VOneCORnet-S
175	ReAlnet04_cornet
176	ReAlnet03_cornet

Benchmark bibtex

None

Ceiling

0.34.

Note that scores are relative to this ceiling.

Data: Kato2026Fil

Metric: error_consistency