diff --git a/spark/src/main/scala/org/apache/spark/sql/comet/operators.scala b/spark/src/main/scala/org/apache/spark/sql/comet/operators.scala
index 0e160faf47..ae334afbee 100644
--- a/spark/src/main/scala/org/apache/spark/sql/comet/operators.scala
+++ b/spark/src/main/scala/org/apache/spark/sql/comet/operators.scala
@@ -1908,11 +1908,12 @@ trait CometBaseAggregate {
       val bufferAttrs = aggFunc.aggBufferAttributes
       aggFunc match {
         case cs: CollectSet =>
-          val elementType = cs.children.head.dataType
+          // Match the native planner's collect argument normalization, including nested fields.
+          val elementType = cs.children.head.dataType.asNullable
           val nativeStateType = ArrayType(elementType, containsNull = true)
           output(bufferIdx) = output(bufferIdx).withDataType(nativeStateType)
         case cl: CollectList =>
-          val elementType = cl.children.head.dataType
+          val elementType = cl.children.head.dataType.asNullable
           val nativeStateType = ArrayType(elementType, containsNull = true)
           output(bufferIdx) = output(bufferIdx).withDataType(nativeStateType)
         case _: Percentile =>
diff --git a/spark/src/test/scala/org/apache/comet/exec/CometAggregateSuite.scala b/spark/src/test/scala/org/apache/comet/exec/CometAggregateSuite.scala
index 362568c77a..1c461ca985 100644
--- a/spark/src/test/scala/org/apache/comet/exec/CometAggregateSuite.scala
+++ b/spark/src/test/scala/org/apache/comet/exec/CometAggregateSuite.scala
@@ -185,6 +185,46 @@ class CometAggregateSuite extends CometTestBase with AdaptiveSparkPlanHelper {
       classOf[LocalTableScanExec])
   }
 
+  test("collect_list and collect_set over non-nullable nested fields survive spilling") {
+    withTempPath { path =>
+      // Keep every group in one input and final partition so aggregation outgrows its memory pool.
+      spark
+        .createDataFrame((0 until 32768).map { i =>
+          (i % 4096, i % 8192, s"${i % 8192}-" + "x" * 256)
+        })
+        .coalesce(1)
+        .write
+        .parquet(path.getAbsolutePath)
+      withParquetTable(path.getAbsolutePath, "tbl") {
+        withSQLConf(
+          SQLConf.ADAPTIVE_EXECUTION_ENABLED.key -> "false",
+          SQLConf.SHUFFLE_PARTITIONS.key -> "1",
+          CometConf.COMET_BATCH_SIZE.key -> "1024",
+          CometConf.COMET_OFFHEAP_MEMORY_POOL_FRACTION.key -> "0.002",
+          CometConf.COMET_RESPECT_DATAFUSION_CONFIGS.key -> "true",
+          "spark.comet.datafusion.execution.sort_spill_reservation_bytes" -> "65536") {
+          // The literal and coalesce create required fields after the Parquet scan, which
+          // otherwise widens field nullability. Sorting removes collect order differences.
+          val struct = "named_struct('flag', true, 'id', coalesce(_2, 0), 'value', _3)"
+          Seq(struct, s"array($struct)").foreach { value =>
+            val (_, cometPlan) = checkSparkAnswerAndOperator(
+              sql(s"""
+              SELECT _1, sort_array(collect_list(s)), sort_array(collect_set(s))
+              FROM (
+                SELECT _1, $value AS s
+                FROM tbl
+              ) GROUP BY _1"""),
+              Seq(classOf[CometHashAggregateExec]))
+            val aggregates = collect(cometPlan) { case agg: CometHashAggregateExec => agg }
+            assert(
+              aggregates.map(_.metrics("spill_count").value).sum > 0L,
+              s"Expected the native collection aggregate to spill:\n$cometPlan")
+          }
+        }
+      }
+    }
+  }
+
   test("grouped collect_list/collect_set over nulls, duplicates and several batches") {
     // Grouped collect_list/collect_set are served by a native GroupsAccumulator rather than one
     // boxed accumulator per group, so the group's identity travels with each row instead of being