diff --git a/invokeai/backend/model_management/convert_ckpt_to_diffusers.py b/invokeai/backend/model_management/convert_ckpt_to_diffusers.py
index dfd7fd100c..aa4dc0ecbc 100644
--- a/invokeai/backend/model_management/convert_ckpt_to_diffusers.py
+++ b/invokeai/backend/model_management/convert_ckpt_to_diffusers.py
@@ -1071,6 +1071,7 @@ def convert_controlnet_checkpoint(
     extract_ema,
     use_linear_projection=None,
     cross_attention_dim=None,
+    precision: torch.dtype=torch.float32,
 ):
     ctrlnet_config = create_unet_diffusers_config(original_config, image_size=image_size, controlnet=True)
     ctrlnet_config["upcast_attention"] = upcast_attention
@@ -1108,9 +1109,9 @@ def convert_controlnet_checkpoint(
 
     controlnet.load_state_dict(converted_ctrl_checkpoint)
 
-    return controlnet
-
+    return controlnet.to(precision)
 
+# TO DO - PASS PRECISION
 def download_from_original_stable_diffusion_ckpt(
     checkpoint_path: str,
     model_version: BaseModelType,
@@ -1120,6 +1121,7 @@ def download_from_original_stable_diffusion_ckpt(
     prediction_type: str = None,
     model_type: str = None,
     extract_ema: bool = False,
+    precision: torch.dtype = torch.float16,
     scheduler_type: str = "pndm",
     num_in_channels: Optional[int] = None,
     upcast_attention: Optional[bool] = None,
@@ -1395,11 +1397,11 @@ def download_from_original_stable_diffusion_ckpt(
     with ctx():
         unet = UNet2DConditionModel(**unet_config)
 
-    # if is_accelerate_available():
-    #     for param_name, param in converted_unet_checkpoint.items():
-    #         set_module_tensor_to_device(unet, param_name, "cpu", value=param)
-    # else:
-    unet.load_state_dict(converted_unet_checkpoint)
+    if is_accelerate_available():
+        for param_name, param in converted_unet_checkpoint.items():
+            set_module_tensor_to_device(unet, param_name, "cpu", value=param)
+    else:
+        unet.load_state_dict(converted_unet_checkpoint)
 
     # Convert the VAE model.
     if vae_path is None:
@@ -1439,10 +1441,10 @@ def download_from_original_stable_diffusion_ckpt(
         if stable_unclip is None:
             if controlnet:
                 pipe = pipeline_class(
-                    vae=vae,
+                    vae=vae.to(precision),
                     text_encoder=text_model,
                     tokenizer=tokenizer,
-                    unet=unet,
+                    unet=unet.to(precision),
                     scheduler=scheduler,
                     controlnet=controlnet,
                     safety_checker=None,
@@ -1451,10 +1453,10 @@ def download_from_original_stable_diffusion_ckpt(
                 )
             else:
                 pipe = pipeline_class(
-                    vae=vae,
+                    vae=vae.to(precision),
                     text_encoder=text_model,
                     tokenizer=tokenizer,
-                    unet=unet,
+                    unet=unet.to(precision),
                     scheduler=scheduler,
                     safety_checker=None,
                     feature_extractor=None,
@@ -1542,10 +1544,10 @@ def download_from_original_stable_diffusion_ckpt(
 
         if controlnet:
             pipe = pipeline_class(
-                vae=vae,
+                vae=vae.to(precision),
                 text_encoder=text_model,
                 tokenizer=tokenizer,
-                unet=unet,
+                unet=unet.to(precision),
                 controlnet=controlnet,
                 scheduler=scheduler,
                 safety_checker=safety_checker,
@@ -1553,10 +1555,10 @@ def download_from_original_stable_diffusion_ckpt(
             )
         else:
             pipe = pipeline_class(
-                vae=vae,
+                vae=vae.to(precision),
                 text_encoder=text_model,
                 tokenizer=tokenizer,
-                unet=unet,
+                unet=unet.to(precision),
                 scheduler=scheduler,
                 safety_checker=safety_checker,
                 feature_extractor=feature_extractor,
@@ -1576,12 +1578,12 @@ def download_from_original_stable_diffusion_ckpt(
             )
 
             pipe = StableDiffusionXLPipeline (
-                vae=vae,
+                vae=vae.to(precision),
                 text_encoder=text_encoder,
                 tokenizer=tokenizer,
                 text_encoder_2=text_encoder_2,
                 tokenizer_2=tokenizer_2,
-                unet=unet,
+                unet=unet.to(precision),
                 scheduler=scheduler,
                 force_zeros_for_empty_prompt=True,
             )
@@ -1598,12 +1600,12 @@ def download_from_original_stable_diffusion_ckpt(
             )
 
             pipe = StableDiffusionXLImg2ImgPipeline(
-                vae=vae,
+                vae=vae.to(precision),
                 text_encoder=text_encoder,
                 tokenizer=tokenizer,
                 text_encoder_2=text_encoder_2,
                 tokenizer_2=tokenizer_2,
-                unet=unet,
+                unet=unet.to(precision),
                 scheduler=scheduler,
                 requires_aesthetics_score=True,
                 force_zeros_for_empty_prompt=False,
@@ -1622,6 +1624,7 @@ def download_controlnet_from_original_ckpt(
     original_config_file: str,
     image_size: int = 512,
     extract_ema: bool = False,
+    precision: torch.dtype = torch.float16,
     num_in_channels: Optional[int] = None,
     upcast_attention: Optional[bool] = None,
     device: str = None,
diff --git a/invokeai/backend/model_management/models/stable_diffusion.py b/invokeai/backend/model_management/models/stable_diffusion.py
index 6a8329e911..cf34686d6f 100644
--- a/invokeai/backend/model_management/models/stable_diffusion.py
+++ b/invokeai/backend/model_management/models/stable_diffusion.py
@@ -237,6 +237,7 @@ class StableDiffusion2Model(DiffusersModel):
             return model_path
 
 # TODO: rework
+# pass precision - currently defaulting to fp16
 def _convert_ckpt_and_cache(
         version: BaseModelType,
         model_config: Union[StableDiffusion1Model.CheckpointConfig,