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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Kato2026Ori-accuracy_distance")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	voneresnet-50-robust	1.0
2	resnet_101_v2	1.0
3	resnet_101_v1	1.0
4	grcnn_109	1.0
5	resnet50_robust_l2_eps1	1.0
6	resnet50_ewconplus_wzc	1.0
7	cvt_cvt-21-224-in1k_4_LucyV4	1.0
8	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	1.0
9	cvt_cvt-13-224-in1k_4_LucyV4	1.0
10	convnext_tiny_imagenet_full_seed-0	1.0
11	antialias-resnet152	1.0
12	efficientnet_b0	1.0
13	deit_base_imagenet_full_seed-0	1.0
14	AdvProp_efficientnet-b8	1.0
15	resnet50_st_wzc_seed7_2_323	1.0
16	voneresnet-50-non_stochastic	1.0
17	resnet_SIN_IN_FT_IN	1.0
18	resnet50-SIN_IN_IN	1.0
19	densenet-121	1.0
20	ijepa_vith14_linhead	1.0
21	densenet-201	1.0
22	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	1.0
23	cvt_cvt-21-384-in1k_4_LucyV4	1.0
24	vonegrcnn_62e_nobn	1.0
25	resnet_152_v2	1.0
26	resnet50_st_wzc_seed6_2_323	1.0
27	resnet50_ewconplus_wzc_seed5_2__323	1.0
28	resnet50_ewconplus_wzc_seed6_2_323	1.0
29	resnet50_ewconplus_wzc_seed2_2__323	1.0
30	resnet101_imagenet_full	1.0
31	resnet_50_v1	1.0
32	resnet50_tutorial	1.0
33	resnet50-sup	1.0
34	convnext_femto_ols:d1_in1k	1.0
35	antialiased-r50	1.0
36	resnet152_imagenet_full	1.0
37	deit_small_imagenet_full_seed-0	1.0
38	cvt_cvt-13-384-in1k_4_LucyV4	1.0
39	resnet50_vicreg_linhead	1.0
40	cv_18_dagger_408_pretrained	1.0
41	seresnext50_32x4d	1.0
42	resnet50_hvs_wzc	1.0
43	focalnet_tiny_lrf_in1k	1.0
44	effnetb1_272x240	1.0
45	Res2Net50_26w_4s	1.0
46	convnext_large_imagenet_full_seed-0	1.0
47	convnext_tiny_sup	1.0
48	AT_efficientnet-b2	1.0
49	AdvProp_efficientnet-b6	1.0
50	AdvProp_efficientnet-b2	1.0
51	resnet50_barlowtwins_linhead	1.0
52	resnet50_st_wzc_2	1.0
53	resnet_50_v1_spiking	1.0
54	convnext_base_fb_in1k	1.0
55	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	1.0
56	deit_large_imagenet_full_seed-0	1.0
57	convnext_small_imagenet_full_seed-0	1.0
58	convnext_base_imagenet_full_seed-0	1.0
59	vonegrcnn_47e	1.0
60	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	1.0
61	resnet50_imagenet_full	1.0
62	grcnn	1.0
63	nasnet_mobile	1.0
64	inception_v3	1.0
65	voneresnet-50	1.0
66	resnet_50_v2	1.0
67	regnety_032	1.0
68	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	1.0
69	vit_base_patch16_clip_224:openai_ft_in1k	1.0
70	pnasnet_large_halfPrecision	1.0
71	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	1.0
72	convnext_tiny:in12k_ft_in1k	1.0
73	AdvProp_efficientnet-b7	1.0
74	resnet50_st_wzc_seed3_2_323	1.0
75	resnet50-SIN_IN	1.0
76	vit_large_clip336_openai	1.0
77	deit3_base_patch16_224_fb_in1k	1.0
78	vit_relpos_base_patch16_clsgap_224:sw_in1k	1.0
79	vit_large_patch14_clip_336:openai_ft_in12k_in1k	1.0
80	vit_large_patch14_clip_224:openai_ft_in1k	1.0
81	convnext_base:clip_laiona_augreg_ft_in1k_384	1.0
82	AdvProp_efficientnet-b4	1.0
83	efficientnet_b1_imagenet_full	1.0
84	convnext_large_clip_laion2b_finelayers	1.0
85	convnext_base_fb_in22k_ft_in1k	1.0
86	vit_large_patch14_clip_224:laion2b_ft_in1k	1.0
87	vit_base_patch16_clip_224:openai_ft_in12k_in1k	1.0
88	resnext101_32x48d_wsl	1.0
89	resnext101_32x8d_wsl	1.0
90	ViT_L_32_imagenet1k	1.0
91	efficientnet_b2_imagenet_full	1.0
92	resnet50_byol_linhead	1.0
93	resnet34_imagenet_full	1.0
94	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	1.0
95	dinov2_vitg14_reg_lc	1.0
96	dinov2_vitg14_lc	1.0
97	vit_large_patch14_clip_336:laion2b_ft_in1k	1.0
98	vit_large_patch14_clip_224:openai_ft_in12k_in1k	1.0
99	resnext101_32x32d_wsl	1.0
100	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	1.0
101	dinov2_vitl14_reg_lc	1.0
102	dinov2_vitl14_lc_res336	1.0
103	deit3_base_patch16_224_fb_in22k_ft_in1k	1.0
104	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	1.0
105	swin_small_patch4_window7_224:ms_in22k_ft_in1k	1.0
106	convnext_xxlarge:clip_laion2b_soup_ft_in1k	1.0
107	convnext_xlarge:fb_in22k_ft_in1k	1.0
108	convnext_large:fb_in22k_ft_in1k	1.0
109	shufflenet_v2_x1_0	1.0
110	resnet50-SIN	1.0
111	vit_huge_clip336_laion	1.0
112	dinov2_vitl14_lc	1.0
113	convnext_large_in22k_supervised	1.0
114	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	1.0
115	cvt_cvt-w24-384-in22k_finetuned-in1k_4	1.0
116	eva02_large_in22k	1.0
117	convnext_xxlarge_clip	1.0
118	resnext101_32x16d_wsl	1.0
119	vgg_16	1.0
120	efficientnet_b0_imagenet_full	1.0
121	resnet50-moclr8deg	1.0
122	eicircuit_resnet18_bn_20260919	1.0
123	resnet50-vitoimagevidnet8	1.0
124	resnet50-VITO-8deg-cc	1.0
125	resnet50_simsiam_linhead	.999
126	resnet18_imagenet_full	.999
127	blt_vs	.999
128	ReAlnet07	.999
129	ReAlnet04	.997
130	custom_model_cv_18_dagger_408	.997
131	resnet50_simclr_linhead_01norm	.991
132	ReAlnet09	.991
133	ReAlnet10	.988
134	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.988
135	ReAlnet08	.988
136	resnet50_robust_l2_eps3	.982
137	imagenet_l2_3_0	.982
138	resnet-50-robust	.982
139	mobilenet_v2_1_4_224	.982
140	convnext_base_fb_in1k_gram_aligned_dinov3	.973
141	resnet_50_v1_spiking_l4a	.969
142	mehrer2020_alexnet_training_seed_04	.959
143	mehrer2020_alexnet_training_seed_02	.940
144	mehrer2020_alexnet_training_seed_01	.936
145	mehrer2020_alexnet_training_seed_05	.925
146	mehrer2020_alexnet_training_seed_03	.921
147	mehrer2020_alexnet_training_seed_01_fov12	.917
148	convnext_small_imagenet_100_seed-0	.906
149	alexnet	.873
150	AlexNet_SIN	.805
151	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.714
152	mehrer2020_alexnet_training_seed_01_fov16	.693
153	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.693
154	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.582
155	AlexNet_SIN_fov12	.492
156	mehrer2020_alexnet_training_seed_01_fov4	.407
157	AlexNet_SIN_fov16	.307
158	alexnet_training_seed_07	.021
159	alexnet_training_seed_09	.005
160	alexnet_training_seed_03	.005
161	alexnet_training_seed_10	.000
162	alexnet_training_seed_06	.000
163	alexnet_training_seed_02	.000
164	alexnet_training_seed_01	.000
165	mobilenet_v2_1_0_128
166	gabor_filter_entropy_4x4_v2_forcedCosine
167	gabor_filter_entropy_4x4_v2
168	dinov2_vitl14_reg_lc_featread
169	deepeisnn_ei_imagenet_resnet18
170	hmax
171	ReAlnet01_cornet
172	compact_resnet50_robust_V4
173	VOneCORnet-S
174	ReAlnet04_cornet
175	ReAlnet01_cornet_fov4
176	ReAlnet03_cornet

Benchmark bibtex

None

Ceiling

0.89.

Note that scores are relative to this ceiling.

Data: Kato2026Ori

Metric: accuracy_distance