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Sample stimuli

How to use

from brainscore_vision import load_benchmark
benchmark = load_benchmark("Marques2020_Ringach2002-orth_pref_ratio")
score = benchmark(my_model)

Benchmark API

Code examples

Model scores

Score Legend Min Alignment Max Alignment

Rank	Model	Score
1	resnet-18-LC_m	.983
2	yudixie_resnet50_rotation_reg_0_240908	.974
3	vit_tiny_r_s16_p8_384:augreg_in21k_ft_in1k	.973
4	yudixie_resnet18_category_class_0_240719	.971
5	vonegrcnn_62e_nobn	.958
6	cvt_cvt-21-384-in1k_4_LucyV4	.954
7	0.5x_resnet-18_LC_w_sh_10_iter	.954
8	yudixie_resnet50_distance_translation_rotation_0_240908	.953
9	efficientnet_b1_imagenet_full	.949
10	yudixie_resnet50_cat_obj_class_all_latents_0_240908	.949
11	yudixie_resnet18_cat_obj_class_all_latents_0_240719	.943
12	convnext_large:fb_in22k_ft_in1k	.944
13	convnext_femto_ols:d1_in1k	.941
14	yudixie_resnet50_category_class_0_240908	.938
15	resnet50_barlowtwins_linhead	.939
16	yudixie_resnet18_translation_reg_0_240719	.938
17	effnetb1_cutmixpatch_SAM_robust32_avge6e8e9e10_manylayers_324x288	.937
18	effnetb1_cutmixpatch_augmix_robust32_e5_324x288	.937
19	xception	.937
20	effnetb1_cutmixrespatch_SAM_robust32_e2_manylayers_324x288	.937
21	effnetb1_cutmixpatch_augmix_robust32_avge4e7_manylayers_324x288	.936
22	effnetb1_cutmixrespatch_SAM_robust32_e10_manylayers_324x288	.936
23	cvt_cvt-21-224-in1k_4_LucyV4	.935
24	resnet50_vicreg_linhead	.935
25	yudixie_resnet50_distance_rotation_0_240908	.932
26	cvt_cvt-13-224-in1k_4_LucyV4	.933
27	compact_vgg19_V4	.932
28	blt_vs	.931
29	resnet50_simsiam_linhead	.930
30	yudixie_resnet50_translation_rotation_0_240908	.928
31	mobilenet_v2_1.3_224-tf	.930
32	mobilenet_v2_1_0_128	.929
33	inception_v1	.926
34	resnet-18-LC_w_sh_1_iter_m	.926
35	resnet-18-LC_1st_conv_m	.926
36	briaai_rmbg_1_4	.926
37	resnet-152_v2-tf	.922
38	vgg_19	.921
39	AdvProp_efficientnet-b6	.921
40	compact_cornets_V4	.921
41	efficientnet-b7	.918
42	AlexNet_SIN	.919
43	resnet50_hvs_wzc	.917
44	BiT-M-R50x3	.916
45	resnet-18-LC_d_w_sh_1x1_conv_init_m	.916
46	fulltest_microblockvf_nobottleneck_freeat_nopretrain_eps2_m4	.915
47	compact_resnet50_V4	.915
48	compact_cornets_IT	.914
49	ReAlnet01_cornet_fov4	.914
50	alexnet	.912
51	yudixie_resnet18_translation_rotation_0_240719	.911
52	convnext_base:clip_laiona_augreg_ft_in1k_384	.911
53	grcnn	.911
54	alexnet_robust_correct	.909
55	resnet50_simclr_linhead_01norm	.906
56	texture_shape_alexnet_trained_on_SIN	.906
57	resnext101_32x8d_wsl	.905
58	alexnet_random_l2_3_perturb	.903
59	cvt_cvt-13-384-in22k_finetuned-in1k_4_LucyV4	.903
60	resnet50_byol_linhead	.902
61	resnet50_ewconplus_wzc	.902
62	resnet-18-LC_w_sh_10_iter_conv_init_m	.903
63	focalnet_tiny_lrf_in1k	.901
64	yudixie_resnet18_object_class_0_240719	.901
65	mobilenet_v2_1.0_160-tf	.901
66	yudixie_resnet50_distance_reg_0_240908	.901
67	AdvProp_efficientnet-b8	.900
68	mehrer2020_alexnet_training_seed_01_fov12	.898
69	resnet50_st_wzc_seed7_2_323	.898
70	omnivore_swinS	.898
71	compact_resnet50_robust_V4	.895
72	resnet50_primary_visual_cortex	.896
73	Res2Net50_26w_4s	.896
74	BiT-S-R50x1	.895
75	resnet50_imagenet_100_seed-0	.894
76	mobilenet_v2_1.0_224-tf	.893
77	yudixie_resnet50_distance_translation_0_240908	.892
78	resnet-18-LC_w_sh_100_iter_conv_init_m	.893
79	alexnet_fov4	.892
80	convnext_base_fb_in22k_ft_in1k_gram_aligned_dinov3	.889
81	convnext_base_fb_in22k_ft_in1k	.889
82	grcnn_robust_v1	.887
83	yudixie_wbh_object_class_scaling_0415_run_0	.888
84	yudixie_resnet18_distance_rotation_0_240719	.886
85	deepeisnn_ei_cifar10_vgg19	.885
86	resnet101	.887
87	compact_vgg19_IT	.885
88	konkle_alexnetgn_ipcl_ref12_supervised_ipcl_aug	.885
89	resnet50_st_wzc_seed6_2_323	.885
90	0.5x_resnet-18_LC_w_sh_100_iter	.884
91	mehrer2020_alexnet_training_seed_03	.883
92	resnet-18-LC_w_sh_1_iter_conv_init_m	.879
93	resnet50-vitoimagevidnet8	.876
94	yudixie_resnet50_translation_reg_0_240908	.876
95	resnet50_ewconplus_wzc_seed6_2_323	.875
96	omnivore_swinB	.874
97	vgg-16-keras	.874
98	alexnet_reduced_aliasing_early_checkpoint	.874
99	barlow-twins-resnet50	.873
100	resnet50_ewconplus_wzc_seed5_2__323	.873
101	resnet18_ecoset_full	.872
102	compact_resnet50_IT	.872
103	vgg_16	.871
104	grcnn_109	.870
105	resnet50_byol	.868
106	resnet50-SIN_IN	.867
107	convnext_small_imagenet_full_seed-0	.867
108	resnet18_fair	.868
109	CORnet-Z	.867
110	grcnn_v2_text_noise	.866
111	alexnet_random_linf8_perturb	.864
112	resnet50_st_wzc_seed3_2_323	.862
113	resnet_50_v2	.862
114	resnet-50_v1-tf	.861
115	alexnet_l2_3_robust	.860
116	resnet-18-LC_w_sh_10_iter_m	.859
117	0.5x_resnet-18_LC_w_sh_1_iter	.858
118	ReAlnet04	.857
119	swin_small_patch4_window7_224:ms_in22k_ft_in1k	.857
120	ReAlnet04_cornet	.857
121	ReAlnet03	.855
122	ReAlnet03_cornet	.856
123	ReAlnet01_cornet_fov16	.855
124	eicircuit_resnet18_bn_20260919	.853
125	0.5x_resnet-18_LC	.853
126	BiT-M-R101x1	.853
127	tf_efficientnetv2_s_in21ft1k_robust_linf12255_400x400	.852
128	mehrer2020_alexnet_training_seed_08	.850
129	inception_v3-tf	.850
130	mehrer2020_alexnet_training_seed_04	.849
131	CORnetZ_CIFAR10_bs32_20_04	.850
132	ReAlnet01	.850
133	resnet50-vicregl0p9	.850
134	ReAlnet08_cornet	.849
135	ReAlnet08	.850
136	mehrer2020_alexnet_training_seed_02	.849
137	ReAlnet01_cornet	.847
138	ReAlnet09	.846
139	ReAlnet09_cornet	.847
140	convnext_tiny_imagenet_full_seed-0	.847
141	resnet50-simclr-vissl	.847
142	ReAlnet02	.847
143	ReAlnet07	.847
144	ReAlnet02_cornet	.846
145	yudixie_resnet50_object_class_0_240908	.846
146	ReAlnet07_cornet	.846
147	inception_v3	.845
148	yudixie_wbh_object_class_scaling_0415_run_3	.844
149	alexnet_linf_8_robust	.844
150	yudixie_resnet18_distance_translation_rotation_0_240719	.843
151	BiT-S-R50x3	.844
152	ReAlnet10	.843
153	resnext101_32x32d_wsl	.842
154	nasnet_large-tf	.842
155	resnet18_imagenet21kP	.841
156	vonealexnet_gaussian_noise_std4_fixed	.839
157	ReAlnet10_cornet	.839
158	alexnet_early_checkpoint	.838
159	compact_resnet50_robust_IT	.837
160	BiT-S-R101x3	.837
161	resnet50_imagenet_10_seed-0	.837
162	ReAlnet06_cornet	.835
163	ReAlnet06	.836
164	AlexNet_SIN_fov4	.835
165	convnext_xxlarge_clip	.836
166	ReAlnet05	.833
167	convnext_large_clip_laion2b_finelayers	.833
168	ReAlnet05_cornet	.832
169	yudixie_wbh_object_class_scaling_0415_run_1	.832
170	resnet101_imagenet_full	.829
171	convnext_tiny_sup	.829
172	antialias-resnet152	.827
173	yudixie_resnet18_distance_translation_0_240719	.826
174	densenet-201	.826
175	convnext_small_imagenet_100_seed-0	.825
176	resnet_50_v1_spiking_l4a	.824
177	resnet_50_v1	.824
178	resnet_50_v1_spiking	.823
179	yudixie_wbh_object_class_scaling_0415_run_2	.823
180	resnet50_ewconplus_wzc_seed2_2__323	.822
181	yudixie_resnet50_imagenet1kpret_0_240908	.821
182	resnet50_tutorial	.822
183	resnet50-sup	.821
184	resnet_50_v1_spiking_l4	.821
185	alexnet_fov12	.821
186	densenet-201-keras	.821
187	AlexNet_SIN_fov12	.820
188	resnet_50_v1_spiking_l3	.820
189	AdvProp_efficientnet-b7	.819
190	CORnet-S	.816
191	mobilenet_v2_0_75_192	.817
192	convnext_xlarge:fb_in22k_ft_in1k	.817
193	resnet50-moclr8deg	.814
194	resnet-50_untrained	.815
195	ReAlnet07_ALL	.814
196	resnet50-vicregl0p75	.812
197	CLIP-RN50	.811
198	ViT_L_32_imagenet1k	.810
199	imagenet_l2_10_0	.810
200	ReAlnet03_ALL	.810
201	vgg-19-keras	.810
202	imagenet_l2_3_0	.810
203	ReAlnet04_ALL	.809
204	ReAlnet08_ALL	.808
205	RN50	.807
206	resnet50	.807
207	ReAlnet10_ALL	.807
208	resnet-50x2_untrained	.806
209	mobilenet_v2_1_4_224	.806
210	effnetb1_cutmix_augmix_sam_e1_5avg_424x377	.805
211	inception_v4-tf	.804
212	ReAlnet05_ALL	.804
213	resnet50_st_wzc_2	.804
214	cornet_s	.803
215	ReAlnet09_ALL	.802
216	ReAlnet02_ALL	.802
217	convnext_large_in22k_supervised	.802
218	ReAlnet01_ALL	.802
219	resnet50-SIN_IN_IN	.800
220	resnet-50-robust	.800
221	mobilenet_v2_1_3_224	.799
222	resnet50_robust_l2_eps1	.796
223	resnet50_random_linf8_perturb	.795
224	deit_small_imagenet_full_seed-0	.795
225	r3m_resnet34_nocrop	.795
226	ReAlnet06_ALL	.795
227	mehrer2020_alexnet_training_seed_09	.795
228	alexnet_fov16	.793
229	resnet50_l2_3_robust	.792
230	resnext101_32x48d_wsl	.789
231	resnet50_linf_8_robust	.787
232	deepeisnn_ei_cifar10_resnet18	.786
233	BiT-S-R152x2	.786
234	resnet50_finetune_cutmix_AVGe2e3_robust_linf8255_e0_247x234	.785
235	convnext_base_fb_in1k	.784
236	resnet50_finetune_cutmix_e3_robust_linf8255_e0_247x234	.784
237	resnet50_robust_l2_eps3	.783
238	antialiased-r50	.782
239	resnet50_random_l2_perturb	.780
240	resnet_SIN_IN_FT_IN	.779
241	resnext101_32x16d_wsl	.780
242	yudixie_wbh_object_class_scaling_0415_imagenet	.779
243	resnet50-vicreg	.779
244	yudixie_resnet18_imagenet1kpret_0_240719	.779
245	resnet34_imagenet_full	.778
246	resnet18_imagenet_full	.776
247	efficientnet_b0	.775
248	convnext_large_imagenet_full_seed-0	.775
249	convnext_base_imagenet_full_seed-0	.772
250	mobilenet_v2_1.0_96	.772
251	VOneCORnet-S	.772
252	convnext_large_mlp:clip_laion2b_augreg_ft_in1k_384	.769
253	texture_shape_resnet50_trained_on_SIN	.769
254	vit_base_patch16_clip_224:openai_ft_in1k	.769
255	densenet-121	.767
256	mobilenet_v2_0_5_224	.767
257	inception_v2-tf	.766
258	voneresnet-50-robust	.764
259	voneresnet-50	.758
260	mobilenet_v2_0.75_192-tf	.757
261	resnet50_linf_4_robust	.756
262	CLIP_resnet50	.756
263	ReAlnet01_cornet_fov12	.755
264	convnext_tiny:in12k_ft_in1k	.755
265	CLIP_resnet50_float32	.755
266	AdvProp_efficientnet-b4	.754
267	mobilenet_v2_1.4_224-tf	.755
268	densenet-169	.754
269	resnet50_ecoset_full	.752
270	resnet-18_untrained	.749
271	deepeisnn_ei_imagenet_resnet18	.750
272	resnet50-VITO-8deg-cc	.747
273	0.5x_resnet-18	.745
274	resnet50-cifar	.743
275	resnet50-SIN	.741
276	SWSL_resnet50	.741
277	dinov2_vitl14_lc_res336	.742
278	resnet50_imagenet_full	.741
279	alexnet_training_seed_01_fov16	.741
280	alexnet_training_seed_01_fov12	.738
281	mobilenet_v2_0_75_224	.739
282	AdvProp_efficientnet-b0	.738
283	resnet152_imagenet_full	.738
284	resnet101_ecoset_full	.735
285	alexnet_training_seed_02	.735
286	resnet-101_v2-tf	.732
287	mobilenet_v2_1.0_192-tf	.730
288	mobilenet_v2_1-4_224_pytorch	.728
289	pnasnet_large-tf	.727
290	alexnet_training_seed_07	.727
291	cvt_cvt-13-384-in1k_4_LucyV4	.725
292	vggface	.725
293	resnet-50_v2-tf	.724
294	resnet-18_test_m	.720
295	pnasnet_large_halfPrecision	.719
296	vit_base_patch16_clip_224:openai_ft_in12k_in1k	.719
297	alexnet_training_seed_04	.719
298	vonegrcnn_47e	.718
299	resnet-152_v1-tf	.716
300	yudixie_resnet18_distance_reg_0_240719	.715
301	alexnet_training_seed_01	.714
302	mobilenet_v2_0.5_192-tf	.715
303	resnet-18-LC_w_sh_100_iter_m	.715
304	voneresnet-50-non_stochastic	.712
305	mobilenet_v2_0.75_128	.713
306	yudixie_resnet50_random_0_240908	.711
307	alexnet_training_seed_09	.710
308	mobilenet_v1_0.25_128	.707
309	vit_relpos_base_patch32_plus_rpn_256:sw_in1k	.707
310	FrankRobWobv0	.705
311	antialiased-rnext101_32x8d	.705
312	AlexNet_SIN_fov16	.705
313	vit_base_patch14_reg4_dinov2-lvd142m	.705
314	resnet-101_v1-tf	.704
315	BiT-S-R152x4	.702
316	vit_large_patch14_clip_224:laion2b_ft_in1k	.701
317	cvt_cvt-w24-384-in22k_finetuned-in1k_4	.701
318	resnet34_ecoset_full	.700
319	BiT-M-R101x3	.698
320	resnet152_ecoset_full	.697
321	BiT-M-R152x4	.697
322	mobilenet_v2_1_0_192	.696
323	SWSL_resnext101_32x8d	.696
324	convnext_small_imagenet_10_seed-0	.695
325	vonegrcnn_52e_full	.693
326	vit_huge_patch14_clip_336:laion2b_ft_in12k_in1k	.693
327	resnet-152_v2_pytorch	.693
328	densenet-121-keras	.692
329	v1-pyr-nodown	.689
330	efficientnet_b0_imagenet_full	.687
331	ijepa_vith14_linhead	.686
332	deit_small_imagenet_100_seed-0	.686
333	yudixie_resnet18_rotation_reg_0_240719	.687
334	yolos_tiny	.682
335	vit_base_patch14_dinov2-lvd142m	.680
336	BiT-S-R101x1	.678
337	konkle_alexnetgn_ipcl_ref01_primary_model	.676
338	my-model	.677
339	mobilenet_v2_0.75_160-tf	.669
340	convnext_xxlarge:clip_laion2b_soup_ft_in1k	.668
341	regnety_032	.667
342	nasnet_mobile-tf	.664
343	resnet50-barlow	.662
344	shufflenet_v2_x1_0	.658
345	BiT-M-R152x2	.658
346	nasnet_mobile	.657
347	vision_transformer_vit_large_patch16_224	.656
348	resnet50_FractalDB	.655
349	vit_huge_clip336_laion	.654
350	CLIP_ViT-B_32	.653
351	densenet-169-keras	.652
352	BiT-M-R50x1	.648
353	effnetv2m_custom384	.640
354	vit_large_patch14_clip_336:openai_ft_in12k_in1k	.639
355	vit_large_patch14_clip_336:laion2b_ft_in1k	.637
356	alexnet_training_seed_10	.636
357	vit_large_patch14_clip_224:laion2b_ft_in12k_in1k	.634
358	eBarlow_lmda_02_1000ep	.633
359	cv_18_dagger_408_pretrained	.632
360	cvt_cvt-21-384-in22k_finetuned-in1k_4_LucyV4	.630
361	dinov2_vitg14_lc	.628
362	mobilenet_v2_0_75_160	.627
363	alexnet_training_seed_03	.627
364	resnet50_moco_v2	.624
365	deit_large_imagenet_full_seed-0	.624
366	omnivore_swinT	.623
367	mobilenet_v2_1_0_224	.622
368	efficientnet_b2_imagenet_full	.619
369	dinov2_vitl14_reg_lc_featread	.615
370	dinov2_vitl14_reg_lc	.615
371	yudixie_resnet18_random_0_240719	.613
372	artResNet18_1	.612
373	seresnext50_32x4d	.613
374	custom_model_cv_18_dagger_408	.612
375	eva02_large_in22k	.610
376	inception_v1-tf	.610
377	convnext_base_fb_in1k_gram_aligned_dinov3	.606
378	vit_large_clip336_openai	.602
379	resnet50_simclr	.602
380	mobilenet_v2_0.35_224	.602
381	deit3_base_patch16_224_fb_in22k_ft_in1k_gram_aligned_dinov3	.598
382	deit3_base_patch16_224_fb_in22k_ft_in1k	.597
383	mobilenet_v2_1.0_128-tf	.596
384	mobilenet_v2_1_0_160	.594
385	effnetb1_272x240	.594
386	vit_large_patch14_clip_224:openai_ft_in1k	.589
387	r3m_resnet34	.585
388	mobilenet_v2_0.5_224-tf	.582
389	resnet-18-LC_conv_init_m	.583
390	alexnet_training_seed_01_fov4	.581
391	dinov2_vitl14_lc	.581
392	vit_huge_patch14_clip_224:laion2b_ft_in12k_in1k	.578
393	convnext_small_imagenet_1_seed-0	.577
394	vit_large_patch14_clip_224:openai_ft_in12k_in1k	.561
395	mobilenet_v2_0_5_192	.559
396	hmax	.553
397	gabor_filter_mean_abs_4x4_v2	.552
398	deit_base_imagenet_full_seed-0	.551
399	vit_relpos_base_patch16_clsgap_224:sw_in1k	.550
400	deit3_base_patch16_224_fb_in1k	.547
401	deit3_base_patch16_224_fb_in1k_gram_aligned_dinov3	.545
402	r3m_resnet50_nocrop	.528
403	AT_efficientnet-b2	.526
404	AdvProp_efficientnet-b2	.525
405	inception_resnet_v2	.521
406	r3m_resnet18	.514
407	r3m_resnet50	.506
408	gabor_filter_entropy_4x4_v2_forcedCosine	.494
409	resnet50_pretrained_with_retinal_waves	.489
410	my-model	.484
411	mobilenet_v2_0.75_96	.481
412	alexnet_training_seed_08	.479
413	vit_base_patch16_dinov3-lvd1689m	.474
414	CORnetZ_CIFAR10	.422
415	mobilenet_v2_0.5_160	.398
416	mobilenet_v2_0.75_224-tf	.397
417	deit_small_imagenet_10_seed-0	.388
418	ViT-B/32	.387
419	resnet50_imagenet_1_seed-0	.325
420	alexnet_training_seed_05	.313
421	alexnet_training_seed_06	.233
422	resnet-18-LC_untrained	.233
423	mobilenet_v2_0.5_128	.038
424	gabor_filter_entropy_4x4_v2	.038
425	gabor_filter_entropy_4x4	.038
426	mobilenet_v2_0.35_160
427	resnet18-supervised
428	fitvid_trained_on_physion
429	openclip
430	resnet50_ImageNet
431	resnet_101_v1
432	regnet_y_400mf
433	tv_efficientnet-b1
434	alexnet_ks_torevert
435	yudixie_resnet50_imagenet1kpret_0_240312
436	resnet_152_v1
437	densenet_201_pytorch
438	inception_v3_pytorch
439	pnasnet_large_pytorch
440	inception_v4
441	nasnet_large
442	deit_small_imagenet_1_seed-0
443	pnasnet_large
444	vonegrcnn_62e_nobn
445	resnet_101_v2
446	vonegrcnn_47e
447	vonegrcnn_52e_full
448	vonegrcnn_47e
449	resnet_152_v2
450	mehrer2020_alexnet_training_seed_01
451	mehrer2020_alexnet_training_seed_01_fov4
452	mehrer2020_alexnet_training_seed_01_fov16
453	mehrer2020_alexnet_training_seed_05
454	mehrer2020_alexnet_training_seed_06
455	mehrer2020_alexnet_training_seed_07
456	mehrer2020_alexnet_training_seed_10
457	pr1_stl10_disentangled_alpha04
458	predictive_coding_pc
459	dinov2_vitg14_reg_lc

Benchmark bibtex

None

Ceiling

0.96.

Note that scores are relative to this ceiling.

Data: Marques2020_Ringach2002

Metric: orth_pref_ratio