diff --git a/test/onnx/test_fx_to_onnx.py b/test/onnx/test_fx_to_onnx.py
index 58646320935..9fb69589f41 100644
--- a/test/onnx/test_fx_to_onnx.py
+++ b/test/onnx/test_fx_to_onnx.py
@@ -650,6 +650,35 @@ class TestFxToOnnx(pytorch_test_common.ExportTestCase):
 
         self.assertTrue(onnx_program.model_signature, torch.export.ExportGraphSignature)
 
+    @common_utils.parametrize(
+        "float8_type",
+        [
+            common_utils.subtest(
+                torch.float8_e5m2,
+                name="torch_float8_e5m2",
+            ),
+            common_utils.subtest(
+                torch.float8_e5m2fnuz,
+                name="torch_float8_e5m2fnuz",
+            ),
+            common_utils.subtest(
+                torch.float8_e4m3fn,
+                name="torch_float8_e4m3fn",
+            ),
+            common_utils.subtest(
+                torch.float8_e4m3fnuz,
+                name="torch_float8_e4m3fnuz",
+            ),
+        ],
+    )
+    def test_float8_support(self, float8_type):
+        class Float8Module(torch.nn.Module):
+            def forward(self, input: torch.Tensor):
+                input = input.to(float8_type)
+                return input + torch.tensor(1.0, dtype=float8_type)
+
+        _ = torch.onnx.dynamo_export(Float8Module(), torch.randn(1, 2, 3, 4))
+
 
 if __name__ == "__main__":
     common_utils.run_tests()
diff --git a/torch/onnx/_internal/fx/type_utils.py b/torch/onnx/_internal/fx/type_utils.py
index d3c11257724..b7f3d6cea64 100644
--- a/torch/onnx/_internal/fx/type_utils.py
+++ b/torch/onnx/_internal/fx/type_utils.py
@@ -124,6 +124,10 @@ _TORCH_DTYPE_TO_COMPATIBLE_ONNX_TYPE_STRINGS: Dict[
     torch.float64: {"tensor(double)"},
     torch.float32: {"tensor(float)"},
     torch.float16: {"tensor(float16)"},
+    torch.float8_e4m3fn: {"tensor(float8_e4m3fn)"},
+    torch.float8_e4m3fnuz: {"tensor(float8_e4m3fnuz)"},
+    torch.float8_e5m2: {"tensor(float8_e5m2)"},
+    torch.float8_e5m2fnuz: {"tensor(float8_e5m2fnuz)"},
     torch.int16: {"tensor(int16)"},
     torch.int32: {"tensor(int32)"},
     torch.int64: {"tensor(int64)"},
@@ -174,6 +178,10 @@ _TORCH_DTYPE_TO_ABBREVIATION = {
     torch.float64: "f64",
     torch.float32: "f32",
     torch.float16: "f16",
+    torch.float8_e4m3fn: "e4m3fn",
+    torch.float8_e4m3fnuz: "e4m3fnuz",
+    torch.float8_e5m2: "f8e5m2",
+    torch.float8_e5m2fnuz: "e5m2fnuz",
     torch.complex32: "c32",
     torch.complex64: "c64",
     torch.complex128: "c128",
@@ -200,6 +208,10 @@ _TORCH_DTYPE_TO_NUMPY_DTYPE = {
 _ONNX_TENSOR_ELEMENT_TYPE_TO_TORCH_DTYPE = {
     onnx.TensorProto.FLOAT: torch.float32,  # type: ignore[attr-defined]
     onnx.TensorProto.FLOAT16: torch.float16,  # type: ignore[attr-defined]
+    onnx.TensorProto.FLOAT8E5M2: torch.float8_e5m2,  # type: ignore[attr-defined]
+    onnx.TensorProto.FLOAT8E5M2FNUZ: torch.float8_e5m2fnuz,  # type: ignore[attr-defined]
+    onnx.TensorProto.FLOAT8E4M3FN: torch.float8_e4m3fn,  # type: ignore[attr-defined]
+    onnx.TensorProto.FLOAT8E4M3FNUZ: torch.float8_e4m3fnuz,  # type: ignore[attr-defined]
     onnx.TensorProto.DOUBLE: torch.float64,  # type: ignore[attr-defined]
     onnx.TensorProto.BOOL: torch.bool,  # type: ignore[attr-defined]
     onnx.TensorProto.UINT8: torch.uint8,  # type: ignore[attr-defined]