diff --git a/modelopt/torch/speculative/plugins/hf_dflash.py b/modelopt/torch/speculative/plugins/hf_dflash.py
index 084040a5e06..a3f4477ea0c 100644
--- a/modelopt/torch/speculative/plugins/hf_dflash.py
+++ b/modelopt/torch/speculative/plugins/hf_dflash.py
@@ -555,7 +555,8 @@ def modify(self, config):
         # lists. After the cast, because `Module.to` casts float buffers and building first
         # would round the RoPE frequencies.
         base_device = self._base_device()
-        if base_device.type != "meta":
+        self._draft_placed = base_device.type != "meta"
+        if self._draft_placed:
             self.dflash_module.to(device=base_device, dtype=self._base_model.dtype)
             self.dflash_module._maybe_init_rotary_emb(device=base_device)
 
@@ -583,10 +584,12 @@ def restore_draft_precision(self):
         placement entirely. A no-op on a freshly converted model.
         """
         base_device = self._base_device()
-        if base_device.type == "meta":
+        # Placing an already-placed draft again would round its fp32 rotary buffer to bf16.
+        if self._draft_placed or base_device.type == "meta":
             return
         self.dflash_module.to(device=base_device, dtype=self._base_model.dtype)
         self.dflash_module._maybe_init_rotary_emb(device=base_device)
+        self._draft_placed = True
 
     # Draft-module entries that legitimately come from the base model rather than the
     # exported draft checkpoint, so their absence (or presence) is not an error.
diff --git a/tests/unit/torch/speculative/plugins/test_hf_dflash.py b/tests/unit/torch/speculative/plugins/test_hf_dflash.py
index 76050c0e568..40f27e05f40 100644
--- a/tests/unit/torch/speculative/plugins/test_hf_dflash.py
+++ b/tests/unit/torch/speculative/plugins/test_hf_dflash.py
@@ -530,6 +530,29 @@ def test_rotary_emb_init_is_idempotent(self):
         assert dflash_mod.rotary_emb is first
         assert not any(b.is_meta for b in dflash_mod.rotary_emb.buffers())
 
+    def test_restore_draft_precision_keeps_fp32_rope_after_convert(self):
+        """On a fresh convert the draft is already placed; re-casting would round RoPE to bf16."""
+        model = get_tiny_llama(num_hidden_layers=4)
+        mtsp.convert(model, [("dflash", get_dflash_config())])
+        inv_freq = model.dflash_module.rotary_emb.inv_freq.clone()
+        assert inv_freq.dtype == torch.float32
+
+        model.restore_draft_precision()
+
+        assert model.dflash_module.rotary_emb.inv_freq.dtype == torch.float32
+        assert torch.equal(model.dflash_module.rotary_emb.inv_freq, inv_freq)
+
+    def test_restore_draft_precision_places_draft_converted_on_meta(self):
+        """After a meta-device convert (the from_pretrained path) it still places the draft."""
+        model = get_tiny_llama(num_hidden_layers=4).to("meta")
+        mtsp.convert(model, [("dflash", get_dflash_config())])
+        model.to_empty(device="cpu")  # stands in for from_pretrained loading the weights
+
+        model.restore_draft_precision()
+
+        assert model.dflash_module.rotary_emb.inv_freq.dtype == torch.float32
+        assert all(p.dtype == torch.bfloat16 for p in model.dflash_module.parameters())
+
 
 class TestBuildTargetLayerIds:
     """Test target layer selection."""