diff --git a/invokeai/app/api/routers/models.py b/invokeai/app/api/routers/models.py
index 872bce30fe..e0b864f8fd 100644
--- a/invokeai/app/api/routers/models.py
+++ b/invokeai/app/api/routers/models.py
@@ -2,13 +2,18 @@
 
 from typing import Literal, Optional, Union
 
-from fastapi import Query, Body, Path
-from fastapi.routing import APIRouter, HTTPException
+from fastapi import Body, Path, Query, Response
+from fastapi.routing import APIRouter
 from pydantic import BaseModel, Field, parse_obj_as
-from ..dependencies import ApiDependencies
+from starlette.exceptions import HTTPException
+
 from invokeai.backend import BaseModelType, ModelType
 from invokeai.backend.model_management import AddModelResult
-from invokeai.backend.model_management.models import MODEL_CONFIGS, OPENAPI_MODEL_CONFIGS, SchedulerPredictionType
+from invokeai.backend.model_management.models import (MODEL_CONFIGS,
+                                                      OPENAPI_MODEL_CONFIGS,
+                                                      SchedulerPredictionType)
+
+from ..dependencies import ApiDependencies
 
 models_router = APIRouter(prefix="/v1/models", tags=["models"])
 
@@ -75,6 +80,7 @@ async def update_model(
     responses= {
         201: {"description" : "The model imported successfully"},
         404: {"description" : "The model could not be found"},
+        424: {"description" : "The model appeared to import successfully, but could not be found in the model manager"},
         409: {"description" : "There is already a model corresponding to this path or repo_id"},
     },
     status_code=201,
@@ -96,9 +102,14 @@ async def import_model(
             items_to_import = items_to_import,
             prediction_type_helper = lambda x: prediction_types.get(prediction_type)
         )
-        if info := installed_models.get(name):
-            logger.info(f'Successfully imported {name}, got {info}')
-            return ImportModelResponse(
+        info = installed_models.get(name)
+
+        if not info:
+            logger.error("Import failed")
+            raise HTTPException(status_code=424)
+        
+        logger.info(f'Successfully imported {name}, got {info}')
+        return ImportModelResponse(
                 name = name,
                 info = info,
                 status = "success",
@@ -124,10 +135,10 @@ async def import_model(
     },
 )
 async def delete_model(
-        base_model: BaseModelType = Path(default='sd-1', description="Base model"),
-        model_type: ModelType = Path(default='main', description="The type of model"),
-        model_name: str = Path(default=None, description="model name"),
-) -> None:
+        base_model: BaseModelType = Path(description="Base model"),
+        model_type: ModelType = Path(description="The type of model"),
+        model_name: str = Path(description="model name"),
+) -> Response:
     """Delete Model"""
     logger = ApiDependencies.invoker.services.logger
     
@@ -137,14 +148,10 @@ async def delete_model(
                                                                  model_type = model_type
                                                                  )
         logger.info(f"Deleted model: {model_name}")
-        raise HTTPException(status_code=204, detail=f"Model '{model_name}' deleted successfully")
+        return Response(status_code=204)
     except KeyError:
         logger.error(f"Model not found: {model_name}")
         raise HTTPException(status_code=404, detail=f"Model '{model_name}' not found")
-    else:
-        logger.info(f"Model deleted: {model_name}")
-        raise HTTPException(status_code=204, detail=f"Model '{model_name}' deleted successfully")
-    
 
             # @socketio.on("convertToDiffusers")
         # def convert_to_diffusers(model_to_convert: dict):