diff --git a/invokeai/backend/model_manager/load/model_loaders/lora.py b/invokeai/backend/model_manager/load/model_loaders/lora.py
index 097aab67a9..be6da03e24 100644
--- a/invokeai/backend/model_manager/load/model_loaders/lora.py
+++ b/invokeai/backend/model_manager/load/model_loaders/lora.py
@@ -86,14 +86,14 @@ class LoRALoader(ModelLoader):
             state_dict = convert_sdxl_keys_to_diffusers_format(state_dict)
             model = lora_model_from_sd_state_dict(state_dict=state_dict)
         elif self._model_base == BaseModelType.Flux:
-            if config.format == ModelFormat.Diffusers:
+            if config.format in [ModelFormat.Diffusers, ModelFormat.OMI]:
                 # HACK(ryand): We set alpha=None for diffusers PEFT format models. These models are typically
                 # distributed as a single file without the associated metadata containing the alpha value. We chose
                 # alpha=None, because this is treated as alpha=rank internally in `LoRALayerBase.scale()`. alpha=rank
                 # is a popular choice. For example, in the diffusers training scripts:
                 # https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/train_dreambooth_lora_flux.py#L1194
                 model = lora_model_from_flux_diffusers_state_dict(state_dict=state_dict, alpha=None)
-            elif config.format in [ModelFormat.LyCORIS, ModelFormat.OMI]:
+            elif config.format == ModelFormat.LyCORIS:
                 if is_state_dict_likely_in_flux_kohya_format(state_dict=state_dict):
                     model = lora_model_from_flux_kohya_state_dict(state_dict=state_dict)
                 elif is_state_dict_likely_in_flux_onetrainer_format(state_dict=state_dict):
diff --git a/invokeai/backend/model_manager/omi.py b/invokeai/backend/model_manager/omi.py
index db12bcddc9..94b339672c 100644
--- a/invokeai/backend/model_manager/omi.py
+++ b/invokeai/backend/model_manager/omi.py
@@ -15,4 +15,6 @@ def convert_from_omi(weights_sd: StateDict, base: BaseModelType):
         BaseModelType.StableDiffusion1: convert_sd_lora_key_sets(),
         BaseModelType.StableDiffusion3: convert_sd3_lora_key_sets(),
     }[base]
-    return lora_util.__convert(weights_sd, keyset, "omi", "diffusers")
+
+    target = "diffusers" # alternatively, "legacy_diffusers"
+    return lora_util.__convert(weights_sd, keyset, "omi", target) # type: ignore