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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Zerbe2026_fmri.V2-ood-ridgecv")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	vit_huge_clip336_laion	.413
2	cvt_cvt-13-384-in1k_4_LucyV4	.402
3	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.400
4	deit_small_imagenet_full_seed-0	.383
5	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.394
6	resnet50-SIN_IN	.392
7	convnext_large:fb_in22k_ft_in1k	.393
8	vit_relpos_base_patch16_clsgap_224:sw_in1k	.391
9	dinov2_vitg14_lc	.391
10	vit_large_clip336_openai	.391
11	dinov2_vitl14_reg_lc_featread	.390
12	dinov2_vitl14_reg_lc	.390
13	dinov2_vitg14_reg_lc	.390
14	antialiased-r50	.388
15	resnet_50_v1_spiking	.389
16	resnet_50_v1	.389
17	resnet50-sup	.389
18	shufflenet_v2_x1_0	.385
19	deit_large_imagenet_full_seed-0	.370
20	focalnet_tiny_lrf_in1k	.385
21	resnet_SIN_IN_FT_IN	.385
22	resnet50-SIN_IN_IN	.385
23	efficientnet_b2_imagenet_full	.383
24	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.383
25	deit_base_imagenet_full_seed-0	.369
26	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.381
27	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.381
28	dinov2_vitl14_lc	.380
29	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.377
30	voneresnet-50	.376
31	Res2Net50_26w_4s	.376
32	convnext_tiny_sup	.375
33	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.375
34	resnext101_32x8d_wsl	.373
35	resnet_50_v2	.372
36	cvt_cvt-21-224-in1k_4_LucyV4	.372
37	voneresnet-50-non_stochastic	.373
38	custom_model_cv_18_dagger_408	.370
39	AdvProp_efficientnet-b4	.370
40	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.370
41	resnext101_32x16d_wsl	.369
42	resnet50_tutorial	.370
43	convnext_tiny:in12k_ft_in1k	.367
44	vit_large_patch14_clip_224:openai_ft_in1k	.367
45	resnet50_ewconplus_wzc	.367
46	resnet50-moclr8deg	.367
47	pnasnet_large_halfPrecision	.367
48	resnet50_robust_l2_eps1	.366
49	AdvProp_efficientnet-b6	.364
50	cvt_cvt-13-224-in1k_4_LucyV4	.365
51	convnext_large_imagenet_full_seed-0	.364
52	convnext_femto_ols:d1_in1k	.364
53	resnet152_imagenet_full	.362
54	densenet-121	.361
55	effnetb1_272x240	.362
56	AdvProp_efficientnet-b8	.360
57	resnet50_imagenet_full	.362
58	resnet50-SIN	.359
59	convnext_base:clip_laiona_augreg_ft_in1k_384	.358
60	cvt_cvt-21-384-in1k_4_LucyV4	.356
61	resnet50-vitoimagevidnet8	.355
62	resnet50-VITO-8deg-cc	.355
63	grcnn	.354
64	resnext101_32x48d_wsl	.353
65	ReAlnet01_cornet	.352
66	ReAlnet04_cornet	.352
67	ReAlnet03_cornet	.351
68	mobilenet_v2_1_4_224	.350
69	convnext_xlarge:fb_in22k_ft_in1k	.348
70	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.346
71	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.345
72	resnext101_32x32d_wsl	.344
73	vit_base_patch16_clip_224:openai_ft_in1k	.343
74	resnet-50-robust	.341
75	convnext_tiny_imagenet_full_seed-0	.342
76	convnext_base_imagenet_full_seed-0	.341
77	vit_large_patch14_clip_336:laion2b_ft_in1k	.340
78	AdvProp_efficientnet-b7	.337
79	convnext_small_imagenet_full_seed-0	.334
80	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.334
81	convnext_xxlarge_clip	.332
82	eva02_large_in22k	.332
83	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.326
84	vit_large_patch14_clip_224:laion2b_ft_in1k	.321
85	alexnet	.320
86	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.316
87	efficientnet_b0	.310
88	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.309
89	AT_efficientnet-b2	.307
90	AdvProp_efficientnet-b2	.307
91	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.305
92	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.294
93	AlexNet_SIN	.288
94	AlexNet_SIN_fov12	.284
95	VOneCORnet-S	.280
96	AlexNet_SIN_fov16	.277
97	ReAlnet01_cornet_fov4	.202
98	alexnet_training_seed_06	.186
99	hmax	.178
100	alexnet_training_seed_03	.180
101	ViT_L_32_imagenet1k	.176
102	alexnet_training_seed_02	.166
103	alexnet_training_seed_09	.163
104	alexnet_training_seed_10	.166
105	alexnet_training_seed_07	.160
106	alexnet_training_seed_01	.160
107	compact_resnet50_robust_V4	.103
108	dinov2_vitl14_lc_res336

Benchmark bibtex

None

Ceiling

0.79.

Note that scores are relative to this ceiling.

Data: Zerbe2026_fmri.V2-ood

Metric: ridgecv