diff --git a/src/relay/transforms/to_mixed_precision.cc b/src/relay/transforms/to_mixed_precision.cc
index 4638ee547706..5026b1bcba79 100644
--- a/src/relay/transforms/to_mixed_precision.cc
+++ b/src/relay/transforms/to_mixed_precision.cc
@@ -350,10 +350,11 @@ class MixedPrecisionPass : public MixedModeMutator {
 
     // TODO(AndrewZhaoLuo): Support ADTs
     // Relay's algebraic data types are not supported yet.
-    ICHECK(!cur_op.as<GlobalVarNode>()       // used to declare functions for recursion
-           && !cur_op.as<ConstructorNode>()  // constructing ADT types
-           && !cur_op.as<VarNode>())         // used for calling recursive functions
-        << "Algebraic Data Types (ADT) are not supported yet for mixed precision pass.";
+    bool isADT = (cur_op.as<GlobalVarNode>()       // used to declare functions for recursion
+                  || cur_op.as<ConstructorNode>()  // constructing ADT types
+                  || cur_op.as<LetNode>()          // used for binding lambdas
+                  || cur_op.as<VarNode>());        // used for calling recursive functions
+    if (isADT) return post;
 
     // Get info on the operation being called:
     // conversion category (int), accumulation dtype (str), output dtype (str)
diff --git a/tests/python/relay/test_to_mixed_precision.py b/tests/python/relay/test_to_mixed_precision.py
index a802eee6d644..4c97642498d9 100644
--- a/tests/python/relay/test_to_mixed_precision.py
+++ b/tests/python/relay/test_to_mixed_precision.py
@@ -49,7 +49,6 @@ def verify_mixed_precision_output_close(
     atol: float = 0,
     keep_orig_output_dtype=False,
 ) -> tvm.runtime.Module:
-
     mod = InferType()(mod)
     result_fp32 = run_module(mod, mod_params)
 
@@ -586,5 +585,39 @@ def test_clip_with_pre_op(target_precision):
     assert tvm.ir.structural_equal(expected_mod, output_mod)
 
 
+def test_loop(target_precision):
+    i = relay.var("i", shape=(), dtype="int32")
+    st = relay.var("st", shape=(relay.Any(), 1), dtype="int32")
+
+    def int32(val):
+        return relay.const(val, "int32")
+
+    def _cond(i, st):
+        return relay.op.min(relay.op.less(i, int32(10)))
+
+    def _body(i, st):
+        i_vec = relay.op.reshape(i, (1, 1))
+        ret = relay.op.concatenate([st, i_vec], axis=0)
+        return i + int32(1), ret
+
+    loop = relay.loops.while_loop(_cond, [i, st], _body)
+    start = relay.var("start", shape=(), dtype="int32")
+    body = loop(start, relay.op.reshape(relay.const(0), newshape=(1, 1)))
+    func = relay.Function([start], relay.TupleGetItem(body, 1))
+    mod = tvm.IRModule()
+    mod["main"] = func
+
+    mod_params = {
+        "start": np.random.uniform(-1, 1, size=()).astype("int32"),
+    }
+    output_mod = verify_mixed_precision_output_close(
+        mod, mod_params, mixed_precision_dtype=target_precision, atol=0.01, rtol=0.01
+    )
+
+    # Create expected module
+    expected_mod = InferType()(mod)
+    assert tvm.ir.structural_equal(expected_mod, output_mod)
+
+
 if __name__ == "__main__":
     tvm.testing.main()