diff --git a/nerfstudio/fields/nerfacto_field.py b/nerfstudio/fields/nerfacto_field.py
index e3273ec9d..da51f417a 100644
--- a/nerfstudio/fields/nerfacto_field.py
+++ b/nerfstudio/fields/nerfacto_field.py
@@ -72,6 +72,9 @@ class TCNNNerfactoField(Field):
         num_layers: number of hidden layers
         hidden_dim: dimension of hidden layers
         geo_feat_dim: output geo feat dimensions
+        num_levels: number of levels of the hashmap for the base mlp
+        max_res: maximum resolution of the hashmap for the base mlp
+        log2_hashmap_size: size of the hashmap for the base mlp
         num_layers_color: number of hidden layers for color network
         hidden_dim_color: dimension of hidden layers for color network
         appearance_embedding_dim: dimension of appearance embedding
@@ -87,6 +90,9 @@ class TCNNNerfactoField(Field):
         num_layers: int = 2,
         hidden_dim: int = 64,
         geo_feat_dim: int = 15,
+        num_levels: int = 16,
+        max_res: int = 1024,
+        log2_hashmap_size: int = 19,
         num_layers_color: int = 3,
         num_layers_transient: int = 2,
         hidden_dim_color: int = 64,
@@ -114,10 +120,7 @@ class TCNNNerfactoField(Field):
         self.use_semantics = use_semantics
         self.use_pred_normals = use_pred_normals
 
-        num_levels = 16
-        max_res = 1024
         base_res = 16
-        log2_hashmap_size = 19
         features_per_level = 2
         growth_factor = np.exp((np.log(max_res) - np.log(base_res)) / (num_levels - 1))
 
diff --git a/nerfstudio/models/nerfacto.py b/nerfstudio/models/nerfacto.py
index 086e3c300..b1e772b03 100644
--- a/nerfstudio/models/nerfacto.py
+++ b/nerfstudio/models/nerfacto.py
@@ -69,6 +69,12 @@ class NerfactoModelConfig(ModelConfig):
     """How far along the ray to stop sampling."""
     background_color: Literal["background", "last_sample"] = "last_sample"
     """Whether to randomize the background color."""
+    num_levels: int = 16
+    """Number of levels of the hashmap for the base mlp."""
+    max_res: int = 1024
+    """Maximum resolution of the hashmap for the base mlp."""
+    log2_hashmap_size: int = 19
+    """Size of the hashmap for the base mlp"""
     num_proposal_samples_per_ray: Tuple[int] = (256, 96)
     """Number of samples per ray for the proposal network."""
     num_nerf_samples_per_ray: int = 48
@@ -128,6 +134,9 @@ class NerfactoModel(Model):
         # Fields
         self.field = TCNNNerfactoField(
             self.scene_box.aabb,
+            num_levels=self.config.num_levels,
+            max_res=self.config.max_res,
+            log2_hashmap_size=self.config.log2_hashmap_size,
             spatial_distortion=scene_contraction,
             num_images=self.num_train_data,
             use_pred_normals=self.config.predict_normals,
diff --git a/nerfstudio/models/semantic_nerfw.py b/nerfstudio/models/semantic_nerfw.py
index 3f9dcad86..941716dc8 100644
--- a/nerfstudio/models/semantic_nerfw.py
+++ b/nerfstudio/models/semantic_nerfw.py
@@ -89,6 +89,9 @@ class SemanticNerfWModel(Model):
         # Fields
         self.field = TCNNNerfactoField(
             self.scene_box.aabb,
+            num_levels=self.config.num_levels,
+            max_res=self.config.max_res,
+            log2_hashmap_size=self.config.log2_hashmap_size,
             spatial_distortion=scene_contraction,
             num_images=self.num_train_data,
             use_average_appearance_embedding=self.config.use_average_appearance_embedding,