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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Kato2026SilTex-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	dinov2_vitl14_lc	.821
2	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.798
3	eva02_large_in22k	.785
4	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.761
5	dinov2_vitg14_reg_lc	.757
6	dinov2_vitl14_lc_res336	.756
7	dinov2_vitl14_reg_lc	.745
8	convnext_xxlarge_clip	.731
9	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.710
10	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.697
11	vit_huge_clip336_laion	.688
12	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.683
13	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.683
14	dinov2_vitg14_lc	.681
15	vit_large_patch14_clip_224:laion2b_ft_in1k	.679
16	resnext101_32x8d_wsl	.652
17	convnext_base_fb_in1k_gram_aligned_dinov3	.633
18	vit_large_patch14_clip_336:laion2b_ft_in1k	.632
19	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.619
20	vit_large_clip336_openai	.615
21	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.608
22	convnext_large_clip_laion2b_finelayers	.607
23	resnext101_32x48d_wsl	.605
24	vit_large_patch14_clip_224:openai_ft_in1k	.598
25	ijepa_vith14_linhead	.591
26	resnext101_32x32d_wsl	.565
27	resnet50_robust_l2_eps3	.562
28	imagenet_l2_3_0	.562
29	resnet-50-robust	.562
30	AdvProp_efficientnet-b7	.537
31	resnext101_32x16d_wsl	.525
32	ViT_L_32_imagenet1k	.522
33	AdvProp_efficientnet-b6	.519
34	convnext_base_fb_in1k	.515
35	convnext_large_in22k_supervised	.508
36	vit_base_patch16_clip_224:openai_ft_in1k	.508
37	AT_efficientnet-b2	.505
38	AdvProp_efficientnet-b2	.505
39	AdvProp_efficientnet-b4	.505
40	deit3_base_patch16_224_fb_in1k	.499
41	vit_relpos_base_patch16_clsgap_224:sw_in1k	.495
42	convnext_base:clip_laiona_augreg_ft_in1k_384	.492
43	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.489
44	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.484
45	resnet50-vitoimagevidnet8	.482
46	resnet50-VITO-8deg-cc	.482
47	cv_18_dagger_408_pretrained	.475
48	resnet_101_v2	.473
49	effnetb1_272x240	.472
50	vonegrcnn_47e	.469
51	convnext_large:fb_in22k_ft_in1k	.465
52	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.465
53	convnext_base_fb_in22k_ft_in1k	.464
54	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.458
55	densenet-201	.455
56	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.452
57	resnet50_st_wzc_2	.451
58	cvt_cvt-21-224-in1k_4_LucyV4	.448
59	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.448
60	convnext_tiny_sup	.447
61	voneresnet-50-robust	.445
62	convnext_xlarge:fb_in22k_ft_in1k	.445
63	convnext_tiny:in12k_ft_in1k	.442
64	resnet50_hvs_wzc	.440
65	AdvProp_efficientnet-b8	.439
66	resnet50_ewconplus_wzc_seed2_2__323	.436
67	regnety_032	.435
68	seresnext50_32x4d	.433
69	resnet50_simsiam_linhead	.433
70	antialias-resnet152	.433
71	resnet50-SIN_IN	.432
72	deit3_base_patch16_224_fb_in22k_ft_in1k	.431
73	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.425
74	resnet_152_v2	.424
75	resnet50_byol_linhead	.423
76	grcnn	.421
77	vonegrcnn_62e_nobn	.420
78	resnet101_imagenet_full	.420
79	pnasnet_large_halfPrecision	.419
80	resnet_101_v1	.419
81	resnet50_st_wzc_seed6_2_323	.414
82	efficientnet_b0	.411
83	deit_base_imagenet_full_seed-0	.403
84	resnet152_imagenet_full	.389
85	resnet34_imagenet_full	.387
86	inception_v3	.386
87	eicircuit_resnet18_bn_20260919	.386
88	ReAlnet04	.384
89	efficientnet_b1_imagenet_full	.383
90	resnet50_robust_l2_eps1	.383
91	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.383
92	resnet50_ewconplus_wzc_seed5_2__323	.380
93	resnet_50_v1	.378
94	resnet50_tutorial	.378
95	resnet50-sup	.378
96	voneresnet-50-non_stochastic	.377
97	convnext_tiny_imagenet_full_seed-0	.370
98	resnet_SIN_IN_FT_IN	.370
99	resnet50-SIN_IN_IN	.370
100	ReAlnet07	.369
101	resnet50_ewconplus_wzc	.364
102	mehrer2020_alexnet_training_seed_01_fov16	.361
103	ReAlnet09	.361
104	cvt_cvt-21-384-in1k_4_LucyV4	.359
105	ReAlnet08	.358
106	ReAlnet10	.357
107	deit_small_imagenet_full_seed-0	.357
108	deit_large_imagenet_full_seed-0	.356
109	convnext_small_imagenet_full_seed-0	.353
110	focalnet_tiny_lrf_in1k	.350
111	mehrer2020_alexnet_training_seed_01_fov12	.347
112	antialiased-r50	.344
113	AlexNet_SIN_fov12	.336
114	resnet_50_v1_spiking	.333
115	resnet50_vicreg_linhead	.331
116	resnet50_imagenet_full	.331
117	resnet50_st_wzc_seed7_2_323	.329
118	resnet50-moclr8deg	.329
119	vgg_16	.324
120	nasnet_mobile	.323
121	efficientnet_b0_imagenet_full	.315
122	convnext_large_imagenet_full_seed-0	.315
123	cvt_cvt-13-384-in1k_4_LucyV4	.309
124	convnext_base_imagenet_full_seed-0	.307
125	Res2Net50_26w_4s	.306
126	resnet18_imagenet_full	.306
127	resnet50_simclr_linhead_01norm	.305
128	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.298
129	resnet50-SIN	.295
130	blt_vs	.288
131	custom_model_cv_18_dagger_408	.287
132	grcnn_109	.287
133	densenet-121	.284
134	mobilenet_v2_1_4_224	.284
135	voneresnet-50	.281
136	efficientnet_b2_imagenet_full	.276
137	AlexNet_SIN	.257
138	resnet_50_v1_spiking_l4a	.255
139	resnet50_ewconplus_wzc_seed6_2_323	.254
140	resnet50_st_wzc_seed3_2_323	.250
141	resnet_50_v2	.249
142	resnet50_barlowtwins_linhead	.229
143	mehrer2020_alexnet_training_seed_03	.226
144	shufflenet_v2_x1_0	.225
145	AlexNet_SIN_fov16	.198
146	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.186
147	mehrer2020_alexnet_training_seed_01	.174
148	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.171
149	cvt_cvt-13-224-in1k_4_LucyV4	.163
150	mehrer2020_alexnet_training_seed_04	.159
151	convnext_femto_ols:d1_in1k	.158
152	mehrer2020_alexnet_training_seed_01_fov4	.157
153	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.149
154	mehrer2020_alexnet_training_seed_02	.131
155	mehrer2020_alexnet_training_seed_05	.117
156	alexnet	.108
157	convnext_small_imagenet_100_seed-0	.085
158	alexnet_training_seed_07	.000
159	alexnet_training_seed_03	.000
160	mobilenet_v2_1_0_128
161	gabor_filter_entropy_4x4_v2_forcedCosine
162	gabor_filter_entropy_4x4_v2
163	dinov2_vitl14_reg_lc_featread
164	deepeisnn_ei_imagenet_resnet18
165	alexnet_training_seed_10
166	alexnet_training_seed_09
167	alexnet_training_seed_06
168	alexnet_training_seed_01
169	alexnet_training_seed_02
170	hmax
171	ReAlnet04_cornet
172	ReAlnet01_cornet
173	compact_resnet50_robust_V4
174	VOneCORnet-S
175	ReAlnet01_cornet_fov4
176	ReAlnet03_cornet

Benchmark bibtex

None

Ceiling

0.43.

Note that scores are relative to this ceiling.

Data: Kato2026SilTex

Metric: error_consistency