diff --git a/tests/test_model_cache.py b/tests/test_model_cache.py
deleted file mode 100644
index 2ced3ea5bd..0000000000
--- a/tests/test_model_cache.py
+++ /dev/null
@@ -1,90 +0,0 @@
-import pytest
-import torch
-
-from enum import Enum
-from invokeai.backend.model_management.model_cache import ModelCache, MODEL_CLASSES
-
-class DummyModelBase(object):
-    '''Base class for dummy component of a diffusers model'''
-    def __init__(self, repo_id):
-        self.repo_id = repo_id
-        self.device = torch.device('cpu')
-
-    @classmethod
-    def from_pretrained(cls,
-                        repo_id:str,
-                        revision:str=None,
-                        subfolder:str=None,
-                        cache_dir:str=None,
-                        ):
-        return cls(repo_id)
-        
-    def to(self, device):
-        self.device = device
-
-class DummyModelType1(DummyModelBase):
-    pass
-
-class DummyModelType2(DummyModelBase):
-    pass
-
-class DummyPipeline(DummyModelBase):
-    '''Dummy pipeline object is a composite of several types'''
-    def __init__(self,repo_id):
-        super().__init__(repo_id)
-        self.dummy_model_type1 = DummyModelType1('dummy/type1')
-        self.dummy_model_type2 = DummyModelType2('dummy/type2')
-
-class DMType(str, Enum):
-    dummy_pipeline = 'dummy_pipeline'
-    type1 = 'dummy_model_type1'
-    type2 = 'dummy_model_type2'
-
-MODEL_CLASSES.update(
-    {
-        DMType.dummy_pipeline: DummyPipeline,
-        DMType.type1: DummyModelType1,
-        DMType.type2: DummyModelType2,
-    }
-)
-
-cache = ModelCache(max_cache_size=4)
-
-def test_pipeline_fetch():
-    assert cache.cache_size()==0
-    with cache.get_model('dummy/pipeline1',DMType.dummy_pipeline) as pipeline1,\
-         cache.get_model('dummy/pipeline1',DMType.dummy_pipeline) as pipeline1a,\
-         cache.get_model('dummy/pipeline2',DMType.dummy_pipeline) as pipeline2:
-        assert pipeline1 is not None, 'get_model() should not return None'
-        assert pipeline1a is not None, 'get_model() should not return None'
-        assert pipeline2 is not None, 'get_model() should not return None'
-        assert type(pipeline1)==DummyPipeline,'get_model() did not return model of expected type'
-        assert pipeline1==pipeline1a,'pipelines with the same repo_id should be the same'
-        assert pipeline1!=pipeline2,'pipelines with different repo_ids should not be the same'
-        assert len(cache.models)==2,'cache should uniquely cache models with same identity'
-    with cache.get_model('dummy/pipeline3',DMType.dummy_pipeline) as pipeline3,\
-         cache.get_model('dummy/pipeline4',DMType.dummy_pipeline) as pipeline4:
-        assert len(cache.models)==4,'cache did not grow as expected'
-
-def test_signatures():
-    with cache.get_model('dummy/pipeline',DMType.dummy_pipeline,revision='main') as pipeline1,\
-         cache.get_model('dummy/pipeline',DMType.dummy_pipeline,revision='fp16') as pipeline2,\
-         cache.get_model('dummy/pipeline',DMType.dummy_pipeline,revision='main',subfolder='foo') as pipeline3:
-        assert pipeline1 != pipeline2,'models are distinguished by their revision'
-        assert pipeline1 != pipeline3,'models are distinguished by their subfolder'
-
-def test_pipeline_device():
-     with cache.get_model('dummy/pipeline1',DMType.type1) as model1:
-         assert model1.device==torch.device('cuda'),'when in context, model device should be in GPU'
-     with cache.get_model('dummy/pipeline1',DMType.type1, gpu_load=False) as model1:
-         assert model1.device==torch.device('cpu'),'when gpu_load=False, model device should be CPU'
-
-def test_submodel_fetch():
-    with cache.get_model(repo_id_or_path='dummy/pipeline1',model_type=DMType.dummy_pipeline) as pipeline,\
-         cache.get_model(repo_id_or_path='dummy/pipeline1',model_type=DMType.dummy_pipeline,submodel=DMType.type1) as part1,\
-         cache.get_model(repo_id_or_path='dummy/pipeline2',model_type=DMType.dummy_pipeline,submodel=DMType.type1) as part2:
-        assert type(part1)==DummyModelType1,'returned submodel is not of expected type'
-        assert part1.device==torch.device('cuda'),'returned submodel should be in the GPU when in context'
-        assert pipeline.dummy_model_type1==part1,'returned submodel should match the corresponding subpart of parent model'
-        assert pipeline.dummy_model_type1!=part2,'returned submodel should not match the subpart of a different parent'
-