diff --git a/doc/source/whatsnew/v3.0.0.rst b/doc/source/whatsnew/v3.0.0.rst
index a7f63d75a047e..ca78e628a2d7b 100644
--- a/doc/source/whatsnew/v3.0.0.rst
+++ b/doc/source/whatsnew/v3.0.0.rst
@@ -701,6 +701,7 @@ I/O
 - Bug in :meth:`.DataFrame.to_json` when ``"index"`` was a value in the :attr:`DataFrame.column` and :attr:`Index.name` was ``None``. Now, this will fail with a ``ValueError`` (:issue:`58925`)
 - Bug in :meth:`DataFrame._repr_html_` which ignored the ``"display.float_format"`` option (:issue:`59876`)
 - Bug in :meth:`DataFrame.from_records` where ``columns`` parameter with numpy structured array was not reordering and filtering out the columns (:issue:`59717`)
+- Bug in :meth:`DataFrame.to_csv` where ``quoting=csv.QUOTE_NONNUMERIC`` adds extra decimal places when ``dtype=float32``, ``dtype=float16``  and ``float_format=None`` in the csv output (:issue:`60699`)
 - Bug in :meth:`DataFrame.to_dict` raises unnecessary ``UserWarning`` when columns are not unique and ``orient='tight'``. (:issue:`58281`)
 - Bug in :meth:`DataFrame.to_excel` when writing empty :class:`DataFrame` with :class:`MultiIndex` on both axes (:issue:`57696`)
 - Bug in :meth:`DataFrame.to_excel` where the :class:`MultiIndex` index with a period level was not a date (:issue:`60099`)
diff --git a/pandas/core/indexes/base.py b/pandas/core/indexes/base.py
index e2f9c5e9868a9..384f24cf2b906 100644
--- a/pandas/core/indexes/base.py
+++ b/pandas/core/indexes/base.py
@@ -7755,13 +7755,15 @@ def get_values_for_csv(
         if float_format is None and decimal == ".":
             mask = isna(values)
 
-            if not quoting:
-                values = values.astype(str)
-            else:
-                values = np.array(values, dtype="object")
+            # GH60699
+            # Ensure quoting don't add extra decimal places in output
+            # for float16, float32
+            if values.dtype in [np.float16, np.float32]:
+                values = np.array(values, dtype="str")
+                values = values.astype(float, copy=False)
 
-            values[mask] = na_rep
             values = values.astype(object, copy=False)
+            values[mask] = na_rep
             return values
 
         from pandas.io.formats.format import FloatArrayFormatter
diff --git a/pandas/tests/frame/methods/test_to_csv.py b/pandas/tests/frame/methods/test_to_csv.py
index 9eafc69013ffe..b3881f97beeeb 100644
--- a/pandas/tests/frame/methods/test_to_csv.py
+++ b/pandas/tests/frame/methods/test_to_csv.py
@@ -1316,6 +1316,71 @@ def test_to_csv_quoting(self):
         expected = tm.convert_rows_list_to_csv_str(expected_rows)
         assert df.to_csv(quoting=csv.QUOTE_ALL) == expected
 
+    @pytest.mark.parametrize(
+        "data, dtype, expected_rows",
+        [
+            # Test Case 1: float16 precision
+            (
+                {"col": [8.57, 0.156, -0.312, 123.3, -54.5, np.nan]},
+                "float16",
+                [
+                    '"","col"',
+                    "0,8.57",
+                    "1,0.156",
+                    "2,-0.312",
+                    "3,123.3",
+                    "4,-54.5",
+                    '5,""',
+                ],
+            ),
+            # Test Case 2: float32 precision
+            (
+                {"col": [8.57, 1.234567, -2.345678, 1e6, -1.5e6, np.nan]},
+                "float32",
+                [
+                    '"","col"',
+                    "0,8.57",
+                    "1,1.234567",
+                    "2,-2.345678",
+                    "3,1000000.0",
+                    "4,-1500000.0",
+                    '5,""',
+                ],
+            ),
+            # Test Case 3: float64 precision
+            (
+                {
+                    "col": [
+                        8.57,
+                        3.141592653589793,
+                        -2.718281828459045,
+                        1.01e12,
+                        -5.67e11,
+                        np.nan,
+                    ]
+                },
+                "float64",
+                [
+                    '"","col"',
+                    "0,8.57",
+                    "1,3.141592653589793",
+                    "2,-2.718281828459045",
+                    "3,1010000000000.0",
+                    "4,-567000000000.0",
+                    '5,""',
+                ],
+            ),
+        ],
+    )
+    def test_to_csv_decimal_and_nonnumeric_quoting(self, data, dtype, expected_rows):
+        # https://github.com/pandas-dev/pandas/issues/60699
+        # combination of float dtype, no special formatting and
+        # quoting is specified (quoting=csv.QUOTE_NONNUMERIC)
+        df = DataFrame(data, dtype=dtype)
+        result = df.to_csv(quoting=csv.QUOTE_NONNUMERIC)
+        expected = tm.convert_rows_list_to_csv_str(expected_rows)
+        assert result == expected
+
     def test_period_index_date_overflow(self):
         # see gh-15982