diff --git a/invokeai/backend/model_manager/load/model_loaders/flux.py b/invokeai/backend/model_manager/load/model_loaders/flux.py
index dcceda5ad21..c7563c2c203 100644
--- a/invokeai/backend/model_manager/load/model_loaders/flux.py
+++ b/invokeai/backend/model_manager/load/model_loaders/flux.py
@@ -32,7 +32,9 @@
 )
 from invokeai.backend.model_manager.load.load_default import ModelLoader
 from invokeai.backend.model_manager.load.model_loader_registry import ModelLoaderRegistry
-from invokeai.backend.model_manager.util.model_util import convert_bundle_to_flux_transformer_checkpoint
+from invokeai.backend.model_manager.util.model_util import (
+    convert_bundle_to_flux_transformer_checkpoint,
+)
 from invokeai.backend.util.silence_warnings import SilenceWarnings
 
 try:
@@ -193,6 +195,11 @@ def _load_from_singlefile(
             sd = load_file(model_path)
             if "model.diffusion_model.double_blocks.0.img_attn.norm.key_norm.scale" in sd:
                 sd = convert_bundle_to_flux_transformer_checkpoint(sd)
+            new_sd_size = sum([ten.nelement() * torch.bfloat16.itemsize for ten in sd.values()])
+            self._ram_cache.make_room(new_sd_size)
+            for k in sd.keys():
+                # We need to cast to bfloat16 due to it being the only currently supported dtype for inference
+                sd[k] = sd[k].to(torch.bfloat16)
             model.load_state_dict(sd, assign=True)
         return model