diff --git a/deepmd/tf/train/trainer.py b/deepmd/tf/train/trainer.py
index e1d7deb04b..8f4f840a12 100644
--- a/deepmd/tf/train/trainer.py
+++ b/deepmd/tf/train/trainer.py
@@ -255,16 +255,7 @@ def build(
                 self.model.data_stat(data, stat_file_path=stat_file_path)
 
             # config the init_frz_model command
-            if self.run_opt.init_mode == "init_from_frz_model":
-                self._init_from_frz_model()
-            elif self.run_opt.init_mode == "init_model":
-                self._init_from_ckpt(self.run_opt.init_model)
-            elif self.run_opt.init_mode == "restart":
-                self._init_from_ckpt(self.run_opt.restart)
-            elif self.run_opt.init_mode == "finetune":
-                self._init_from_pretrained_model(
-                    data=data, origin_type_map=origin_type_map
-                )
+            self._init_from_run_opt(data=data, origin_type_map=origin_type_map)
 
             # neighbor_stat is moved to train.py as duplicated
         else:
@@ -880,6 +871,27 @@ def _get_place_holders(self, data_dict: dict) -> None:
                 tf.float32, name="t_find_" + kk
             )
 
+    def _init_from_run_opt(
+        self,
+        data: DeepmdDataSystem,
+        origin_type_map: list[str] | None = None,
+    ) -> None:
+        """Dispatch checkpoint pre-inspection based on the run-option init mode.
+
+        The mode strings must match the values produced by
+        :class:`deepmd.tf.train.run_options.RunOptions` exactly; a mismatch
+        silently skips the pre-inspection (see ``_init_from_ckpt``) that detects
+        compressed-checkpoint metadata before graph construction.
+        """
+        if self.run_opt.init_mode == "init_from_frz_model":
+            self._init_from_frz_model()
+        elif self.run_opt.init_mode == "init_from_model":
+            self._init_from_ckpt(self.run_opt.init_model)
+        elif self.run_opt.init_mode == "restart":
+            self._init_from_ckpt(self.run_opt.restart)
+        elif self.run_opt.init_mode == "finetune":
+            self._init_from_pretrained_model(data=data, origin_type_map=origin_type_map)
+
     def _init_from_frz_model(self) -> None:
         try:
             graph, graph_def = load_graph_def(self.run_opt.init_frz_model)
diff --git a/source/tests/tf/test_trainer_init_mode.py b/source/tests/tf/test_trainer_init_mode.py
new file mode 100644
index 0000000000..fa86363de3
--- /dev/null
+++ b/source/tests/tf/test_trainer_init_mode.py
@@ -0,0 +1,73 @@
+# SPDX-License-Identifier: LGPL-3.0-or-later
+"""Regression test for the TF trainer init-mode dispatch.
+
+``RunOptions`` records ``--init-model`` as ``init_mode == "init_from_model"``,
+but ``DPTrainer`` used to dispatch on the literal ``"init_model"``.  The
+mismatch silently skipped ``_init_from_ckpt`` for ``--init-model``, so the
+compressed-checkpoint pre-inspection that sets ``ckpt_meta`` before graph
+construction never ran.  This checks that each init mode routes to the right
+initializer, using the mode strings ``RunOptions`` actually produces.
+"""
+
+import types
+import unittest
+from unittest import (
+    mock,
+)
+
+from deepmd.tf.train.trainer import (
+    DPTrainer,
+)
+
+
+def _dispatch(init_mode: str) -> str | None:
+    """Run the trainer's init-mode dispatch for ``init_mode`` and report the route.
+
+    A bare ``DPTrainer`` instance is used (constructor bypassed) with the three
+    concrete initializers patched to record which one fires; the return value is
+    the name of the initializer that was called (or ``None`` for scratch).
+    """
+    trainer = DPTrainer.__new__(DPTrainer)
+    trainer.run_opt = types.SimpleNamespace(
+        init_mode=init_mode,
+        init_model="some/init.ckpt",
+        restart="some/restart.ckpt",
+        init_frz_model="some/frozen.pb",
+        finetune="some/pretrained.pb",
+    )
+    with (
+        mock.patch.object(DPTrainer, "_init_from_frz_model") as frz,
+        mock.patch.object(DPTrainer, "_init_from_ckpt") as ckpt,
+        mock.patch.object(DPTrainer, "_init_from_pretrained_model") as pre,
+    ):
+        trainer._init_from_run_opt(data=None, origin_type_map=None)
+        if frz.called:
+            return "frz"
+        if ckpt.called:
+            return f"ckpt:{ckpt.call_args.args[0]}"
+        if pre.called:
+            return "pretrained"
+    return None
+
+
+class TestTrainerInitMode(unittest.TestCase):
+    def test_init_from_model_uses_ckpt(self) -> None:
+        # RunOptions sets this string for `dp train --init-model`; it must reach
+        # _init_from_ckpt so compressed-checkpoint metadata is pre-inspected.
+        self.assertEqual(_dispatch("init_from_model"), "ckpt:some/init.ckpt")
+
+    def test_restart_uses_ckpt(self) -> None:
+        self.assertEqual(_dispatch("restart"), "ckpt:some/restart.ckpt")
+
+    def test_init_from_frz_model_uses_frz(self) -> None:
+        self.assertEqual(_dispatch("init_from_frz_model"), "frz")
+
+    def test_finetune_uses_pretrained(self) -> None:
+        self.assertEqual(_dispatch("finetune"), "pretrained")
+
+    def test_scratch_is_noop(self) -> None:
+        self.assertIsNone(_dispatch("init_from_scratch"))
+
+
+if __name__ == "__main__":
+    unittest.main()