diff --git a/timm/models/mlp_mixer.py b/timm/models/mlp_mixer.py
index 87edbfd6..248568fc 100644
--- a/timm/models/mlp_mixer.py
+++ b/timm/models/mlp_mixer.py
@@ -60,15 +60,6 @@ default_cfgs = dict(
         url='https://github.com/rwightman/pytorch-image-models/releases/download/v0.1-vitjx/jx_mixer_l16_224_in21k-846aa33c.pth',
         num_classes=21843
     ),
-    # Mixer ImageNet-21K-P pretraining
-    mixer_b16_224_miil_in21k=_cfg(
-    url='https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ImageNet_21K_P/models/timm/mixer_b16_224_miil_in21k.pth',
-    mean=(0, 0, 0), std=(1, 1, 1), crop_pct=0.875, interpolation='bilinear', num_classes=11221,
-    ),
-    mixer_b16_224_miil=_cfg(
-    url='https://miil-public-eu.oss-eu-central-1.aliyuncs.com/model-zoo/ImageNet_21K_P/models/timm/mixer_b16_224_miil.pth',
-    mean=(0, 0, 0), std=(1, 1, 1), crop_pct=0.875, interpolation='bilinear',
-    ),
 )
 
 
@@ -264,21 +255,3 @@ def mixer_l16_224_in21k(pretrained=False, **kwargs):
     model_args = dict(patch_size=16, num_blocks=24, hidden_dim=1024, tokens_dim=512, channels_dim=4096, **kwargs)
     model = _create_mixer('mixer_l16_224_in21k', pretrained=pretrained, **model_args)
     return model
-
-@register_model
-def mixer_b16_224_miil(pretrained=False, **kwargs):
-    """ Mixer-B/16 224x224. ImageNet-21k pretrained weights.
-    Weights taken from: https://github.com/Alibaba-MIIL/ImageNet21K
-    """
-    model_args = dict(patch_size=16, num_blocks=12, hidden_dim=768, tokens_dim=384, channels_dim=3072, **kwargs)
-    model = _create_mixer('mixer_b16_224_miil', pretrained=pretrained, **model_args)
-    return model
-
-@register_model
-def mixer_b16_224_miil_in21k(pretrained=False, **kwargs):
-    """ Mixer-B/16 224x224. ImageNet-1k pretrained weights.
-    Weights taken from: https://github.com/Alibaba-MIIL/ImageNet21K
-    """
-    model_args = dict(patch_size=16, num_blocks=12, hidden_dim=768, tokens_dim=384, channels_dim=3072, **kwargs)
-    model = _create_mixer('mixer_b16_224_miil_in21k', pretrained=pretrained, **model_args)
-    return model
\ No newline at end of file