diff --git a/test/test_meta.py b/test/test_meta.py
index 4532bb35677..f6487ae6619 100644
--- a/test/test_meta.py
+++ b/test/test_meta.py
@@ -440,6 +440,9 @@ def run_meta_crossref(
         if func is torch.tensor_split:
             # Use original indices_or_sections, this argument is data dependent
             meta_args = (meta_args[0], args[1]) + meta_args[2:]
+        elif func is torch.ops.aten.repeat_interleave.Tensor:
+            if kwargs.get("output_size", None) is None:
+                meta_args = args
         try:
             # Suppress warnings, this doesn't matter for test_meta.py
             # but it does matter if you want to use this decorator
@@ -840,7 +843,6 @@ meta_dispatch_expected_failures = {
     aten.polar.default: {f64, f32},
     aten.prelu.default: {bf16, f64, f32},
     aten.relu.default: {i64, bf16, u8, f32, i8, f64, i16, i32},
-    aten.repeat_interleave.Tensor: {c64, i64, c128, bf16, f16, u8, b8, f32, i8, f64, i16, i32},
     aten.roll.default: {i64, bf16, f16, u8, b8, f32, i8, f64, i16, i32},
     aten.rrelu_with_noise.default: {bf16, f64, f32},
     aten.searchsorted.Tensor: {i64, bf16, f16, u8, f32, i8, f64, i16, i32},
diff --git a/torch/_meta_registrations.py b/torch/_meta_registrations.py
index cc6b8f986a6..6a3edb53fde 100644
--- a/torch/_meta_registrations.py
+++ b/torch/_meta_registrations.py
@@ -135,3 +135,11 @@ def meta_adaptive_avg_pool2d(self, output_size):
 def meta_adaptive_avg_pool3d(self, output_size):
     check(self.ndim == 4 or self.ndim == 5, f"Expected 4D or 5D tensor, but got {self.shape}")
     return self.new_empty(self.shape[:-3] + tuple(output_size))
+
+@torch.library.impl(meta_lib, "repeat_interleave.Tensor")
+def meta_repeat_interleave_Tensor(repeats, output_size=None):
+    if output_size is None:
+        raise RuntimeError(
+            "cannot repeat_interleave a meta tensor without output_size"
+        )
+    return repeats.new_empty(output_size)