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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Zerbe2026_fmri.V1-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	.425
2	cvt_cvt-13-384-in1k_4_LucyV4	.424
3	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.415
4	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.414
5	vit_relpos_base_patch16_clsgap_224:sw_in1k	.407
6	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.404
7	densenet-121	.402
8	resnext101_32x16d_wsl	.400
9	convnext_large:fb_in22k_ft_in1k	.397
10	shufflenet_v2_x1_0	.397
11	vit_large_clip336_openai	.397
12	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.393
13	vit_large_patch14_clip_224:openai_ft_in1k	.394
14	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.392
15	AdvProp_efficientnet-b6	.391
16	resnet_50_v1_spiking	.391
17	resnet50-sup	.391
18	resnet_50_v1	.391
19	resnet50_tutorial	.391
20	resnext101_32x48d_wsl	.390
21	resnet50-SIN_IN_IN	.390
22	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.388
23	convnext_femto_ols:d1_in1k	.386
24	antialiased-r50	.384
25	grcnn	.382
26	convnext_xlarge:fb_in22k_ft_in1k	.380
27	focalnet_tiny_lrf_in1k	.381
28	cvt_cvt-13-224-in1k_4_LucyV4	.379
29	efficientnet_b2_imagenet_full	.377
30	cvt_cvt-21-224-in1k_4_LucyV4	.377
31	AdvProp_efficientnet-b4	.375
32	cvt_cvt-21-384-in1k_4_LucyV4	.376
33	resnet50-SIN	.376
34	custom_model_cv_18_dagger_408	.375
35	resnet_SIN_IN_FT_IN	.376
36	effnetb1_272x240	.374
37	convnext_tiny_sup	.371
38	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.370
39	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.370
40	pnasnet_large_halfPrecision	.369
41	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.371
42	convnext_base_imagenet_full_seed-0	.365
43	convnext_small_imagenet_full_seed-0	.362
44	dinov2_vitg14_reg_lc	.363
45	mobilenet_v2_1_4_224	.361
46	resnet50-moclr8deg	.359
47	AdvProp_efficientnet-b7	.360
48	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.360
49	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.357
50	dinov2_vitg14_lc	.357
51	voneresnet-50	.356
52	vit_large_patch14_clip_336:laion2b_ft_in1k	.353
53	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.352
54	vit_large_patch14_clip_224:laion2b_ft_in1k	.354
55	resnet50_robust_l2_eps1	.350
56	efficientnet_b0	.350
57	dinov2_vitl14_reg_lc	.350
58	eva02_large_in22k	.349
59	AT_efficientnet-b2	.347
60	AdvProp_efficientnet-b2	.347
61	vit_base_patch16_clip_224:openai_ft_in1k	.348
62	dinov2_vitl14_lc	.349
63	resnext101_32x32d_wsl	.346
64	convnext_tiny:in12k_ft_in1k	.344
65	deit_base_imagenet_full_seed-0	.334
66	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.343
67	resnext101_32x8d_wsl	.340
68	resnet50-VITO-8deg-cc	.340
69	resnet50-vitoimagevidnet8	.340
70	AdvProp_efficientnet-b8	.338
71	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.341
72	dinov2_vitl14_lc_res336	.336
73	resnet_50_v2	.334
74	convnext_tiny_imagenet_full_seed-0	.332
75	convnext_large_imagenet_full_seed-0	.331
76	resnet-50-robust	.333
77	deit_small_imagenet_full_seed-0	.320
78	convnext_base:clip_laiona_augreg_ft_in1k_384	.330
79	resnet50-SIN_IN	.321
80	deit_large_imagenet_full_seed-0	.308
81	Res2Net50_26w_4s	.317
82	ReAlnet03_cornet	.312
83	ReAlnet01_cornet	.312
84	ReAlnet04_cornet	.312
85	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.310
86	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.310
87	resnet50_ewconplus_wzc	.308
88	alexnet	.299
89	AlexNet_SIN_fov16	.297
90	ViT_L_32_imagenet1k	.296
91	AlexNet_SIN	.288
92	resnet152_imagenet_full	.288
93	AlexNet_SIN_fov12	.284
94	compact_resnet50_robust_V4	.266
95	resnet50_imagenet_full	.236
96	alexnet_training_seed_02	.213
97	alexnet_training_seed_06	.206
98	alexnet_training_seed_09	.203
99	alexnet_training_seed_07	.202
100	alexnet_training_seed_01	.200
101	alexnet_training_seed_10	.196
102	alexnet_training_seed_03	.178
103	hmax	.163
104	ReAlnet01_cornet_fov4	.163
105	voneresnet-50-non_stochastic	.130
106	VOneCORnet-S	.084
107	convnext_xxlarge_clip
108	dinov2_vitl14_reg_lc_featread

Benchmark bibtex

None

Ceiling

0.81.

Note that scores are relative to this ceiling.

Data: Zerbe2026_fmri.V1-ood

Metric: ridgecv