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Sample stimuli

How to use

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

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	eva02_large_in22k	1.0
2	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.970
3	vit_huge_clip336_laion	.964
4	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.956
5	convnext_large_in22k_supervised	.954
6	alexnet_training_seed_03	.949
7	dinov2_vitg14_reg_lc	.948
8	convnext_xxlarge_clip	.948
9	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.947
10	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.939
11	dinov2_vitl14_reg_lc	.934
12	vit_large_patch14_clip_336:laion2b_ft_in1k	.909
13	convnext_large:fb_in22k_ft_in1k	.904
14	dinov2_vitg14_lc	.899
15	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.897
16	vit_large_clip336_openai	.897
17	convnext_xlarge:fb_in22k_ft_in1k	.892
18	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.878
19	vit_large_patch14_clip_224:laion2b_ft_in1k	.859
20	cv_18_dagger_408_pretrained	.849
21	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.845
22	convnext_base_fb_in22k_ft_in1k	.844
23	dinov2_vitl14_lc	.839
24	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.838
25	dinov2_vitl14_lc_res336	.833
26	vit_large_patch14_clip_224:openai_ft_in1k	.826
27	cvt_cvt-21-384-in1k_4_LucyV4	.816
28	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.815
29	resnet50_robust_l2_eps3	.812
30	imagenet_l2_3_0	.812
31	resnet-50-robust	.812
32	ViT_L_32_imagenet1k	.801
33	convnext_large_clip_laion2b_finelayers	.800
34	cvt_cvt-13-224-in1k_4_LucyV4	.792
35	vit_relpos_base_patch16_clsgap_224:sw_in1k	.790
36	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.786
37	deit3_base_patch16_224_fb_in1k	.783
38	vit_base_patch16_clip_224:openai_ft_in1k	.776
39	voneresnet-50-robust	.771
40	resnext101_32x48d_wsl	.771
41	resnext101_32x16d_wsl	.763
42	pnasnet_large_halfPrecision	.756
43	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.748
44	ijepa_vith14_linhead	.745
45	deit3_base_patch16_224_fb_in22k_ft_in1k	.744
46	convnext_base_imagenet_full_seed-0	.744
47	convnext_base:clip_laiona_augreg_ft_in1k_384	.738
48	resnext101_32x32d_wsl	.736
49	convnext_base_fb_in1k	.736
50	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.734
51	custom_model_cv_18_dagger_408	.729
52	focalnet_tiny_lrf_in1k	.726
53	regnety_032	.726
54	efficientnet_b1_imagenet_full	.725
55	resnext101_32x8d_wsl	.724
56	convnext_tiny_sup	.724
57	deit_large_imagenet_full_seed-0	.724
58	convnext_tiny:in12k_ft_in1k	.722
59	convnext_small_imagenet_full_seed-0	.714
60	grcnn	.712
61	cvt_cvt-13-384-in1k_4_LucyV4	.710
62	resnet_101_v2	.709
63	convnext_large_imagenet_full_seed-0	.705
64	deit_small_imagenet_full_seed-0	.705
65	efficientnet_b2_imagenet_full	.701
66	resnet50_st_wzc_2	.698
67	resnet50_ewconplus_wzc_seed5_2__323	.697
68	AdvProp_efficientnet-b7	.694
69	resnet50_robust_l2_eps1	.694
70	effnetb1_272x240	.692
71	densenet-201	.684
72	resnet152_imagenet_full	.682
73	eicircuit_resnet18_bn_20260919	.679
74	seresnext50_32x4d	.679
75	mehrer2020_alexnet_training_seed_03	.679
76	AdvProp_efficientnet-b6	.676
77	resnet50-SIN_IN	.675
78	resnet50_st_wzc_seed3_2_323	.673
79	resnet50_ewconplus_wzc_seed6_2_323	.670
80	antialias-resnet152	.670
81	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.669
82	resnet_101_v1	.668
83	densenet-121	.666
84	resnet50_hvs_wzc	.664
85	cvt_cvt-21-224-in1k_4_LucyV4	.653
86	mehrer2020_alexnet_training_seed_01	.648
87	deit_base_imagenet_full_seed-0	.648
88	voneresnet-50-non_stochastic	.648
89	resnet18_imagenet_full	.642
90	vonegrcnn_47e	.641
91	vonegrcnn_62e_nobn	.639
92	convnext_tiny_imagenet_full_seed-0	.639
93	resnet50_ewconplus_wzc	.639
94	convnext_base_fb_in1k_gram_aligned_dinov3	.638
95	resnet50_st_wzc_seed6_2_323	.635
96	mehrer2020_alexnet_training_seed_05	.634
97	convnext_femto_ols:d1_in1k	.634
98	resnet101_imagenet_full	.633
99	resnet50_st_wzc_seed7_2_323	.629
100	AdvProp_efficientnet-b2	.628
101	AT_efficientnet-b2	.628
102	resnet50_tutorial	.627
103	resnet_50_v1	.627
104	resnet50-sup	.627
105	vgg_16	.624
106	voneresnet-50	.623
107	resnet_50_v1_spiking	.623
108	resnet_SIN_IN_FT_IN	.622
109	resnet50-SIN_IN_IN	.622
110	resnet34_imagenet_full	.622
111	AdvProp_efficientnet-b4	.615
112	convnext_small_imagenet_100_seed-0	.615
113	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.615
114	grcnn_109	.614
115	resnet50-vitoimagevidnet8	.612
116	resnet50-VITO-8deg-cc	.612
117	shufflenet_v2_x1_0	.603
118	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.603
119	resnet_152_v2	.601
120	Res2Net50_26w_4s	.600
121	antialiased-r50	.598
122	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.596
123	blt_vs	.593
124	AlexNet_SIN_fov12	.582
125	mehrer2020_alexnet_training_seed_02	.578
126	resnet50_ewconplus_wzc_seed2_2__323	.578
127	ReAlnet07	.575
128	AdvProp_efficientnet-b8	.568
129	ReAlnet10	.567
130	ReAlnet08	.565
131	ReAlnet04	.554
132	mehrer2020_alexnet_training_seed_01_fov12	.554
133	ReAlnet09	.553
134	efficientnet_b0	.552
135	efficientnet_b0_imagenet_full	.545
136	resnet50_imagenet_full	.545
137	mehrer2020_alexnet_training_seed_04	.540
138	mehrer2020_alexnet_training_seed_01_fov16	.528
139	mehrer2020_alexnet_training_seed_01_fov4	.516
140	resnet50_vicreg_linhead	.512
141	resnet50_byol_linhead	.510
142	nasnet_mobile	.506
143	alexnet	.496
144	resnet_50_v2	.495
145	resnet50_simsiam_linhead	.492
146	AlexNet_SIN_fov16	.478
147	resnet50-moclr8deg	.478
148	resnet50_simclr_linhead_01norm	.470
149	resnet50_barlowtwins_linhead	.468
150	resnet_50_v1_spiking_l4a	.466
151	AlexNet_SIN	.464
152	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.452
153	inception_v3	.420
154	resnet50-SIN	.417
155	mobilenet_v2_1_4_224	.378
156	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.368
157	alexnet_training_seed_09	.352
158	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.318
159	alexnet_training_seed_07	.211
160	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.187
161	mobilenet_v2_1_0_128
162	dinov2_vitl14_reg_lc_featread
163	gabor_filter_entropy_4x4_v2_forcedCosine
164	gabor_filter_entropy_4x4_v2
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	compact_resnet50_robust_V4
172	ReAlnet01_cornet
173	VOneCORnet-S
174	ReAlnet04_cornet
175	ReAlnet03_cornet
176	ReAlnet01_cornet_fov4

Benchmark bibtex

None

Ceiling

0.95.

Note that scores are relative to this ceiling.

Data: Kato2026SilTex

Metric: accuracy_distance