diff --git a/CHANGELOG.md b/CHANGELOG.md
index 49c47b1e3..01acf553a 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -49,6 +49,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Fix existing templates
 - Add optional data insert to `Table`
 - Make Lance vector searcher as plugin.
+- Remove job dependencies from job metadata
 
 #### New Features & Functionality
 
@@ -77,6 +78,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Updated llm_finetuning template
 - Add sql table length exceed limit and uuid truncation.
 - Add ci workflow to test templates
+- Add deploy flag in model.
 
 #### Bug Fixes
 
diff --git a/superduper/base/event.py b/superduper/base/event.py
index dd95fe2b9..f52552e4e 100644
--- a/superduper/base/event.py
+++ b/superduper/base/event.py
@@ -17,6 +17,7 @@ def dict(self):
         _base_dict = dc.asdict(self)
         if 'time' in _base_dict:
             _base_dict['time'] = str(_base_dict['time'])
+        _base_dict.pop('dependencies', None)
         return {
             **_base_dict,
             'genus': self.genus,
diff --git a/superduper/components/component.py b/superduper/components/component.py
index a80062b06..3c958a416 100644
--- a/superduper/components/component.py
+++ b/superduper/components/component.py
@@ -559,7 +559,6 @@ def declare_component(self, cluster):
         if self.cache:
             logging.info(f'Adding {self.type_id}: {self.identifier} to cache')
             cluster.cache.put(self)
-            cluster.compute.put(self)
 
     def on_load(self, db: Datalayer) -> None:
         """Called when this component is loaded from the data store.
diff --git a/superduper/components/model.py b/superduper/components/model.py
index aa68be068..0c8fc96d5 100644
--- a/superduper/components/model.py
+++ b/superduper/components/model.py
@@ -372,6 +372,7 @@ class Model(Component, metaclass=ModelMeta):
                   ``compute_kwargs`` on a distributed cluster.
     :param trainer: `Trainer` instance to use for training.
     :param example: An example to auto-determine the schema/ datatype.
+    :param deploy: Creates a standalone class instance on compute cluster.
     """
 
     type_id: t.ClassVar[str] = 'model'
@@ -387,6 +388,7 @@ class Model(Component, metaclass=ModelMeta):
     serve: bool = False
     trainer: t.Optional[Trainer] = None
     example: dc.InitVar[t.Any | None] = None
+    deploy: bool = False
 
     def __post_init__(self, db, artifacts, example):
         super().__post_init__(db, artifacts)
@@ -407,7 +409,9 @@ def _wrapper(self, data):
 
     def declare_component(self, cluster):
         """Declare model on compute."""
-        cluster.compute.put(self)
+        super().declare_component(cluster)
+        if self.deploy or self.serve:
+            cluster.compute.put(self)
 
     @abstractmethod
     def predict(self, *args, **kwargs) -> t.Any: