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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Kato2026LinFil-error_consistency")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	vit_large_patch14_clip_336:laion2b_ft_in1k	.845
2	vit_large_patch14_clip_224:laion2b_ft_in1k	.839
3	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.831
4	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.811
5	convnext_xlarge:fb_in22k_ft_in1k	.798
6	vit_huge_clip336_laion	.793
7	resnext101_32x32d_wsl	.782
8	vit_large_patch14_clip_224:openai_ft_in1k	.780
9	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.778
10	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.778
11	vit_base_patch16_clip_224:openai_ft_in1k	.776
12	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.767
13	convnext_large_clip_laion2b_finelayers	.765
14	convnext_xxlarge_clip	.731
15	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.722
16	eva02_large_in22k	.708
17	dinov2_vitl14_lc	.690
18	vit_large_clip336_openai	.683
19	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.680
20	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.677
21	dinov2_vitl14_lc_res336	.627
22	dinov2_vitl14_reg_lc	.609
23	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.605
24	resnext101_32x48d_wsl	.601
25	regnety_032	.596
26	convnext_base_fb_in1k_gram_aligned_dinov3	.587
27	resnext101_32x16d_wsl	.578
28	dinov2_vitg14_lc	.573
29	convnext_base_fb_in1k	.566
30	convnext_base:clip_laiona_augreg_ft_in1k_384	.561
31	convnext_base_fb_in22k_ft_in1k	.561
32	convnext_large:fb_in22k_ft_in1k	.557
33	dinov2_vitg14_reg_lc	.534
34	convnext_small_imagenet_full_seed-0	.523
35	resnext101_32x8d_wsl	.516
36	convnext_large_in22k_supervised	.499
37	AdvProp_efficientnet-b7	.465
38	convnext_tiny:in12k_ft_in1k	.459
39	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.446
40	AdvProp_efficientnet-b4	.438
41	convnext_base_imagenet_full_seed-0	.433
42	AdvProp_efficientnet-b2	.414
43	AT_efficientnet-b2	.414
44	convnext_large_imagenet_full_seed-0	.410
45	AdvProp_efficientnet-b6	.405
46	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.395
47	deit3_base_patch16_224_fb_in1k	.394
48	resnet50-SIN	.370
49	vit_relpos_base_patch16_clsgap_224:sw_in1k	.358
50	focalnet_tiny_lrf_in1k	.351
51	deit3_base_patch16_224_fb_in22k_ft_in1k	.348
52	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.337
53	AdvProp_efficientnet-b8	.322
54	cvt_cvt-13-224-in1k_4_LucyV4	.297
55	resnet50_st_wzc_2	.283
56	convnext_tiny_imagenet_full_seed-0	.266
57	resnet50-vitoimagevidnet8	.262
58	resnet50-VITO-8deg-cc	.262
59	seresnext50_32x4d	.261
60	cv_18_dagger_408_pretrained	.249
61	resnet50_byol_linhead	.236
62	resnet50_barlowtwins_linhead	.222
63	resnet50-moclr8deg	.215
64	AlexNet_SIN_fov12	.210
65	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.210
66	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.188
67	resnet50_hvs_wzc	.185
68	resnet50_vicreg_linhead	.183
69	deit_large_imagenet_full_seed-0	.179
70	resnet50_simclr_linhead_01norm	.177
71	resnet152_imagenet_full	.171
72	densenet-201	.165
73	resnet50_ewconplus_wzc_seed2_2__323	.164
74	mehrer2020_alexnet_training_seed_03	.163
75	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.163
76	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.162
77	convnext_tiny_sup	.162
78	mehrer2020_alexnet_training_seed_01_fov12	.160
79	mobilenet_v2_1_4_224	.160
80	antialias-resnet152	.148
81	resnet50_robust_l2_eps3	.147
82	imagenet_l2_3_0	.147
83	resnet-50-robust	.147
84	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.147
85	mehrer2020_alexnet_training_seed_05	.140
86	resnet50_ewconplus_wzc_seed6_2_323	.136
87	inception_v3	.121
88	resnet50-SIN_IN	.116
89	mehrer2020_alexnet_training_seed_04	.115
90	cvt_cvt-13-384-in1k_4_LucyV4	.113
91	resnet_50_v2	.111
92	vonegrcnn_62e_nobn	.109
93	resnet50_ewconplus_wzc	.098
94	efficientnet_b2_imagenet_full	.098
95	efficientnet_b0_imagenet_full	.097
96	voneresnet-50-robust	.097
97	cvt_cvt-21-384-in1k_4_LucyV4	.094
98	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.092
99	blt_vs	.090
100	effnetb1_272x240	.087
101	resnet50_robust_l2_eps1	.085
102	efficientnet_b1_imagenet_full	.083
103	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.083
104	vonegrcnn_47e	.082
105	Res2Net50_26w_4s	.082
106	resnet50_st_wzc_seed6_2_323	.080
107	pnasnet_large_halfPrecision	.078
108	resnet50_simsiam_linhead	.073
109	mehrer2020_alexnet_training_seed_01_fov4	.073
110	densenet-121	.071
111	voneresnet-50-non_stochastic	.064
112	resnet50_st_wzc_seed3_2_323	.063
113	resnet50_st_wzc_seed7_2_323	.063
114	resnet_101_v2	.059
115	cvt_cvt-21-224-in1k_4_LucyV4	.054
116	resnet_50_v1_spiking_l4a	.053
117	efficientnet_b0	.051
118	grcnn	.051
119	resnet_SIN_IN_FT_IN	.050
120	resnet50-SIN_IN_IN	.050
121	AlexNet_SIN	.047
122	ViT_L_32_imagenet1k	.046
123	custom_model_cv_18_dagger_408	.046
124	nasnet_mobile	.045
125	ReAlnet09	.045
126	ReAlnet10	.044
127	mehrer2020_alexnet_training_seed_01_fov16	.043
128	resnet50_imagenet_full	.043
129	resnet_50_v1_spiking	.043
130	mehrer2020_alexnet_training_seed_01	.037
131	vgg_16	.037
132	ReAlnet08	.035
133	convnext_small_imagenet_100_seed-0	.034
134	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.032
135	resnet34_imagenet_full	.028
136	eicircuit_resnet18_bn_20260919	.024
137	resnet18_imagenet_full	.024
138	resnet_50_v1	.023
139	resnet50_tutorial	.023
140	resnet50-sup	.023
141	mehrer2020_alexnet_training_seed_02	.021
142	antialiased-r50	.021
143	alexnet	.021
144	deit_base_imagenet_full_seed-0	.019
145	convnext_femto_ols:d1_in1k	.017
146	ReAlnet07	.011
147	ReAlnet04	.010
148	resnet_101_v1	.008
149	resnet50_ewconplus_wzc_seed5_2__323	.008
150	grcnn_109	.005
151	deit_small_imagenet_full_seed-0	.005
152	AlexNet_SIN_fov16	.000
153	resnet101_imagenet_full	.000
154	voneresnet-50	.000
155	ijepa_vith14_linhead	.000
156	resnet_152_v2	.000
157	alexnet_training_seed_09	.000
158	alexnet_training_seed_03	.000
159	alexnet_training_seed_07	.000
160	shufflenet_v2_x1_0	.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_10
167	alexnet_training_seed_06
168	alexnet_training_seed_02
169	alexnet_training_seed_01
170	hmax
171	ReAlnet01_cornet
172	compact_resnet50_robust_V4
173	VOneCORnet-S
174	ReAlnet04_cornet
175	ReAlnet03_cornet
176	ReAlnet01_cornet_fov4

Benchmark bibtex

None

Ceiling

0.44.

Note that scores are relative to this ceiling.

Data: Kato2026LinFil

Metric: error_consistency