diff --git a/python/tvm/relax/frontend/torch/exported_program_translator.py b/python/tvm/relax/frontend/torch/exported_program_translator.py
index 26121ecdea10..cc9217c9f5f8 100644
--- a/python/tvm/relax/frontend/torch/exported_program_translator.py
+++ b/python/tvm/relax/frontend/torch/exported_program_translator.py
@@ -368,6 +368,7 @@ def create_convert_map(
             "argmin.default": self._argmax_argmin(relax.op.argmin),
             "where.self": self._where,
             # tensor manipulation
+            "argsort.default": self._argsort,
             "cat.default": self._cat,
             "chunk.default": self._chunk,
             "clamp.Tensor": self._clamp,
@@ -390,6 +391,7 @@ def create_convert_map(
             "squeeze.dim": self._squeeze,
             "take.default": self._take,
             "tile.default": self._tile,
+            "topk.default": self._topk,
             "transpose.int": self._transpose,
             "unsqueeze.default": lambda node: self.block_builder.emit(
                 relax.op.expand_dims(self.env[node.args[0]], node.args[1])
diff --git a/tests/python/relax/test_frontend_from_exported_program.py b/tests/python/relax/test_frontend_from_exported_program.py
index cc2f669d32e0..081b82b3c563 100644
--- a/tests/python/relax/test_frontend_from_exported_program.py
+++ b/tests/python/relax/test_frontend_from_exported_program.py
@@ -3859,5 +3859,54 @@ def main(
     verify_model(Where(), (condition, x, y), {}, Expected)
 
 
+def test_argsort():
+    class Argsort(Module):
+        def forward(self, x):
+            return torch.argsort(x, dim=1, descending=True)
+
+    @tvm.script.ir_module
+    class Expected:
+        @R.function
+        def main(x: R.Tensor((5, 3), dtype="float32")) -> R.Tuple(R.Tensor((5, 3), dtype="int32")):
+            with R.dataflow():
+                lv: R.Tensor((5, 3), dtype="int32") = R.argsort(
+                    x, axis=1, descending=True, dtype="int32"
+                )
+                gv: R.Tuple(R.Tensor((5, 3), dtype="int32")) = (lv,)
+                R.output(gv)
+            return gv
+
+    example_args = (torch.randn(5, 3, dtype=torch.float32),)
+    verify_model(Argsort(), example_args, {}, Expected)
+
+
+def test_topk():
+    class Topk(Module):
+        def forward(self, x):
+            return torch.topk(x, k=2, dim=1, largest=True, sorted=True)
+
+    @tvm.script.ir_module
+    class Expected:
+        @R.function
+        def main(
+            x: R.Tensor((5, 3), dtype="float32")
+        ) -> R.Tuple(R.Tensor((5, 2), dtype="float32"), R.Tensor((5, 2), dtype="int64")):
+            with R.dataflow():
+                lv: R.Tuple(
+                    R.Tensor((5, 2), dtype="float32"), R.Tensor((5, 2), dtype="int64")
+                ) = R.topk(x, k=2, axis=1, ret_type="both", largest=True, dtype="int64")
+                lv1: R.Tensor((5, 2), dtype="float32") = lv[0]
+                lv2: R.Tensor((5, 2), dtype="int64") = lv[1]
+                gv: R.Tuple(R.Tensor((5, 2), dtype="float32"), R.Tensor((5, 2), dtype="int64")) = (
+                    lv1,
+                    lv2,
+                )
+                R.output(gv)
+            return gv
+
+    example_args = (torch.randn(5, 3, dtype=torch.float32),)
+    verify_model(Topk(), example_args, {}, Expected)
+
+
 if __name__ == "__main__":
     tvm.testing.main()