diff --git a/modelconverter/__main__.py b/modelconverter/__main__.py
index d0b82ca..aa87273 100644
--- a/modelconverter/__main__.py
+++ b/modelconverter/__main__.py
@@ -217,13 +217,10 @@ def extract_preprocessing(
 
         dai_type = encoding.from_.value
         if dai_type != "NONE":
-            if (
-                inp.data_type == DataType.FLOAT32
-                or inp.data_type == DataType.INT8
-            ):
-                type = "888"
-            elif inp.data_type == DataType.FLOAT16:
+            if inp.data_type == DataType.FLOAT16:
                 type = "F16F16F16"
+            else:
+                type = "888"
             dai_type += type
             dai_type += "i" if layout == "NHWC" else "p"
 
diff --git a/modelconverter/utils/nn_archive.py b/modelconverter/utils/nn_archive.py
index 8fd1bc9..8a85161 100644
--- a/modelconverter/utils/nn_archive.py
+++ b/modelconverter/utils/nn_archive.py
@@ -18,6 +18,7 @@
 from modelconverter.utils.constants import MISC_DIR
 from modelconverter.utils.layout import guess_new_layout, make_default_layout
 from modelconverter.utils.metadata import get_metadata
+from modelconverter.utils.types import DataType
 
 logger = logging.getLogger(__name__)
 
@@ -191,7 +192,7 @@ def modelconverter_config_to_nn(
     cfg = config.stages[main_stage_key]
 
     archive_cfg = {
-        "config_version": CONFIG_VERSION.__args__[-1],  # type: ignore
+        "config_version": CONFIG_VERSION,
         "model": {
             "metadata": {
                 "name": model_name.stem,
@@ -205,21 +206,25 @@ def modelconverter_config_to_nn(
 
     for inp in cfg.inputs:
         new_shape = model_metadata.input_shapes[inp.name]
-        # new_dtype = model_metadata.input_dtypes[inp.name]
         if inp.shape is not None and not any(s == 0 for s in inp.shape):
             assert inp.layout is not None
             layout = guess_new_layout(inp.layout, inp.shape, new_shape)
         else:
             layout = make_default_layout(new_shape)
+        dai_type = inp.encoding.to.value
+        if inp.data_type == DataType.FLOAT16:
+            type = "F16F16F16"
+        else:
+            type = "888"
+        dai_type += type
+        dai_type += "i" if layout == "NHWC" else "p"
 
         archive_cfg["model"]["inputs"].append(
             {
                 "name": inp.name,
                 "shape": new_shape,
                 "layout": layout,
-                # "dtype": new_dtype.value,
                 "dtype": inp.data_type.value,
-                # "dtype": "float32",
                 "input_type": "image",
                 "preprocessing": {
                     "mean": [0 for _ in inp.mean_values]
@@ -230,14 +235,14 @@ def modelconverter_config_to_nn(
                         if inp.scale_values
                         else None
                     ),
-                    "reverse_channels": False,
-                    "interleaved_to_planar": False,
+                    "reverse_channels": inp.encoding.from_ != inp.encoding.to,
+                    "interleaved_to_planar": layout == "NHWC",
+                    "dai_type": dai_type,
                 },
             }
         )
     for out in cfg.outputs:
         new_shape = model_metadata.output_shapes[out.name]
-        # new_dtype = model_metadata.output_dtypes[out.name]
         if out.shape is not None and not any(s == 0 for s in out.shape):
             assert out.layout is not None
             layout = guess_new_layout(out.layout, out.shape, new_shape)
@@ -249,9 +254,7 @@ def modelconverter_config_to_nn(
                 "name": out.name,
                 "shape": new_shape,
                 "layout": layout,
-                # "dtype": new_dtype.value,
                 "dtype": out.data_type.value,
-                # "dtype": "float32",
             }
         )
 
@@ -284,7 +287,7 @@ def archive_from_model(model_path: Path) -> NNArchiveConfig:
     metadata = get_metadata(model_path)
 
     archive_cfg = {
-        "config_version": "1.0",
+        "config_version": CONFIG_VERSION,
         "model": {
             "metadata": {
                 "name": model_path.stem,
@@ -302,13 +305,14 @@ def archive_from_model(model_path: Path) -> NNArchiveConfig:
                 "name": name,
                 "shape": shape,
                 "layout": make_default_layout(shape),
-                "dtype": "float32",
+                "dtype": metadata.input_dtypes[name].value,
                 "input_type": "image",
                 "preprocessing": {
                     "mean": None,
                     "scale": None,
-                    "reverse_channels": False,
-                    "interleaved_to_planar": False,
+                    "reverse_channels": None,
+                    "interleaved_to_planar": None,
+                    "dai_type": None,
                 },
             }
         )
@@ -319,7 +323,7 @@ def archive_from_model(model_path: Path) -> NNArchiveConfig:
                 "name": name,
                 "shape": shape,
                 "layout": make_default_layout(shape),
-                "dtype": "float32",
+                "dtype": metadata.output_dtypes[name].value,
             }
         )