diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index 752d08a526d8c..35634cca21f86 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -1167,6 +1167,7 @@ Groupby/resample/rolling
 - Bug in :meth:`.Resampler.interpolate` on a :class:`DataFrame` with non-uniform sampling and/or indices not aligning with the resulting resampled index would result in wrong interpolation (:issue:`21351`)
 - Bug in :meth:`.Series.rolling` when used with a :class:`.BaseIndexer` subclass and computing min/max (:issue:`46726`)
 - Bug in :meth:`DataFrame.ewm` and :meth:`Series.ewm` when passed ``times`` and aggregation functions other than mean (:issue:`51695`)
+- Bug in :meth:`DataFrame.resample.asfreq` where fixed-frequency indexes with ``origin`` ignored alignment and returned incorrect values. Now ``origin`` and ``offset`` are respected. (:issue:`62725`)
 - Bug in :meth:`DataFrame.resample` and :meth:`Series.resample` were not keeping the index name when the index had :class:`ArrowDtype` timestamp dtype (:issue:`61222`)
 - Bug in :meth:`DataFrame.resample` changing index type to :class:`MultiIndex` when the dataframe is empty and using an upsample method (:issue:`55572`)
 - Bug in :meth:`DataFrameGroupBy.agg` and :meth:`SeriesGroupBy.agg` that was returning numpy dtype values when input values are pyarrow dtype values, instead of returning pyarrow dtype values. (:issue:`53030`)
diff --git a/pandas/core/resample.py b/pandas/core/resample.py
index 2694b581a6707..f84bedda8d00c 100644
--- a/pandas/core/resample.py
+++ b/pandas/core/resample.py
@@ -2136,11 +2136,12 @@ def _upsample(self, method, limit: int | None = None, fill_value=None):
         binner = self.binner
         res_index = self._adjust_binner_for_upsample(binner)
 
-        # if we have the same frequency as our axis, then we are equal sampling
+        # if index exactly matches target grid (same freq & alignment), use fast path
         if (
             limit is None
             and to_offset(ax.inferred_freq) == self.freq
             and len(obj) == len(res_index)
+            and obj.index.equals(res_index)
         ):
             result = obj.copy()
             result.index = res_index
diff --git a/pandas/tests/resample/test_resample_api.py b/pandas/tests/resample/test_resample_api.py
index 845b5ad7acc00..69a20443db344 100644
--- a/pandas/tests/resample/test_resample_api.py
+++ b/pandas/tests/resample/test_resample_api.py
@@ -989,3 +989,30 @@ def test_resample_empty():
     )
     result = df.resample("8h").mean()
     tm.assert_frame_equal(result, expected)
+
+
+def test_asfreq_respects_origin_with_fixed_freq_all_seconds_equal():
+    # GH#62725: Ensure Resampler.asfreq respects origin="start_day"
+    # when all datetimes share identical seconds values.
+    idx = [
+        datetime(2025, 10, 17, 17, 15, 10),
+        datetime(2025, 10, 17, 17, 16, 10),
+        datetime(2025, 10, 17, 17, 17, 10),
+    ]
+    df = DataFrame({"value": [0, 1, 2]}, index=idx)
+
+    result = df.resample("1min", origin="start_day").asfreq()
+
+    # Expected index: list of Timestamps, matching dtype
+    exp_idx = pd.DatetimeIndex(
+        [
+            pd.Timestamp("2025-10-17 17:15:00"),
+            pd.Timestamp("2025-10-17 17:16:00"),
+            pd.Timestamp("2025-10-17 17:17:00"),
+        ],
+        dtype=result.index.dtype,
+        freq="min",
+    )
+
+    exp = DataFrame({"value": [np.nan, np.nan, np.nan]}, index=exp_idx)
+    tm.assert_frame_equal(result, exp)