diff --git a/autogalaxy/imaging/model/analysis.py b/autogalaxy/imaging/model/analysis.py
index 2d7aa011..e2bb1e96 100644
--- a/autogalaxy/imaging/model/analysis.py
+++ b/autogalaxy/imaging/model/analysis.py
@@ -27,6 +27,9 @@
 from autogalaxy.imaging.fit_imaging import FitImaging
 
 
+_FIT_IMAGING_PYTREES_REGISTERED = False
+
+
 class AnalysisImaging(AnalysisDataset):
     Result = ResultImaging
     Visualizer = VisualizerImaging
@@ -209,11 +212,38 @@ def _register_fit_imaging_pytrees() -> None:
         analysis — ride as aux so JAX does not recurse into them. Everything
         else (``galaxies``, ``dataset_model`` and the autoarray wrappers they
         carry) is dynamic per fit.
+
+        Idempotent — guarded by the module-level
+        ``_FIT_IMAGING_PYTREES_REGISTERED`` flag so repeated calls from each
+        ``fit_from`` invocation are cheap. ``DatasetModel`` may already be
+        registered by ``autofit.jax.pytrees.register_model`` (its
+        ``_REGISTERED_INSTANCE_CLASSES`` set is independent of autoarray's
+        ``_pytree_registered_classes``); cross-populate so
+        ``register_instance_pytree`` short-circuits instead of asking JAX to
+        register it twice. Mirrors the defense in
+        ``autogalaxy/ellipse/model/analysis.py``.
         """
-        from autoarray.abstract_ndarray import register_instance_pytree
+        global _FIT_IMAGING_PYTREES_REGISTERED
+        if _FIT_IMAGING_PYTREES_REGISTERED:
+            return
+
+        from autoarray.abstract_ndarray import (
+            register_instance_pytree,
+            _pytree_registered_classes,
+        )
         from autoarray.dataset.dataset_model import DatasetModel
         from autogalaxy.analysis.jax_pytrees import register_galaxies_pytree
 
+        try:
+            from autofit.jax.pytrees import (
+                _REGISTERED_INSTANCE_CLASSES as _af_registered,
+            )
+        except ImportError:
+            _af_registered = set()
+
+        if DatasetModel in _af_registered:
+            _pytree_registered_classes.add(DatasetModel)
+
         register_instance_pytree(
             FitImaging,
             no_flatten=("dataset", "adapt_images", "settings"),
@@ -221,6 +251,8 @@ def _register_fit_imaging_pytrees() -> None:
         register_instance_pytree(DatasetModel)
         register_galaxies_pytree()
 
+        _FIT_IMAGING_PYTREES_REGISTERED = True
+
     def save_attributes(self, paths: af.DirectoryPaths):
         """
         Before the non-linear search begins, this routine saves attributes of the `Analysis` object to the `files`
diff --git a/autogalaxy/interferometer/model/analysis.py b/autogalaxy/interferometer/model/analysis.py
index a59902cc..b67d6d90 100644
--- a/autogalaxy/interferometer/model/analysis.py
+++ b/autogalaxy/interferometer/model/analysis.py
@@ -30,6 +30,9 @@
 logger.setLevel(level="INFO")
 
 
+_FIT_INTERFEROMETER_PYTREES_REGISTERED = False
+
+
 class AnalysisInterferometer(AnalysisDataset):
     Result = ResultInterferometer
     Visualizer = VisualizerInterferometer
@@ -173,11 +176,33 @@ def _register_fit_interferometer_pytrees() -> None:
         analysis — ride as aux so JAX does not recurse into them. Everything
         else (``galaxies`` and the autoarray wrappers it carries) is dynamic
         per fit.
+
+        Idempotent — guarded by the module-level
+        ``_FIT_INTERFEROMETER_PYTREES_REGISTERED`` flag. See
+        ``autogalaxy/imaging/model/analysis.py`` for the cross-registration
+        rationale.
         """
-        from autoarray.abstract_ndarray import register_instance_pytree
+        global _FIT_INTERFEROMETER_PYTREES_REGISTERED
+        if _FIT_INTERFEROMETER_PYTREES_REGISTERED:
+            return
+
+        from autoarray.abstract_ndarray import (
+            register_instance_pytree,
+            _pytree_registered_classes,
+        )
         from autoarray.dataset.dataset_model import DatasetModel
         from autogalaxy.analysis.jax_pytrees import register_galaxies_pytree
 
+        try:
+            from autofit.jax.pytrees import (
+                _REGISTERED_INSTANCE_CLASSES as _af_registered,
+            )
+        except ImportError:
+            _af_registered = set()
+
+        if DatasetModel in _af_registered:
+            _pytree_registered_classes.add(DatasetModel)
+
         register_instance_pytree(
             FitInterferometer,
             no_flatten=("dataset", "adapt_images", "settings"),
@@ -185,6 +210,8 @@ def _register_fit_interferometer_pytrees() -> None:
         register_instance_pytree(DatasetModel)
         register_galaxies_pytree()
 
+        _FIT_INTERFEROMETER_PYTREES_REGISTERED = True
+
     def save_attributes(self, paths: af.DirectoryPaths):
         """
         Before the model-fit begins, this routine saves attributes of the `Analysis` object to the `files` folder