diff --git a/native/spark-expr/src/agg_funcs/avg_decimal.rs b/native/spark-expr/src/agg_funcs/avg_decimal.rs
index 773ddea050..08e335f427 100644
--- a/native/spark-expr/src/agg_funcs/avg_decimal.rs
+++ b/native/spark-expr/src/agg_funcs/avg_decimal.rs
@@ -207,6 +207,12 @@ impl AggregateUDFImpl for AvgDecimal {
     fn return_type(&self, arg_types: &[DataType]) -> Result<DataType> {
         avg_return_type(self.name(), &arg_types[0])
     }
+
+    fn is_nullable(&self) -> bool {
+        // In Spark, Sum.nullable and Average.nullable both return true irrespective of ANSI mode.
+        // AvgDecimal is always nullable because overflows can cause null values.
+        true
+    }
 }
 
 /// An accumulator to compute the average for decimals
diff --git a/native/spark-expr/src/agg_funcs/sum_decimal.rs b/native/spark-expr/src/agg_funcs/sum_decimal.rs
index bf5569b00b..56a735493c 100644
--- a/native/spark-expr/src/agg_funcs/sum_decimal.rs
+++ b/native/spark-expr/src/agg_funcs/sum_decimal.rs
@@ -164,7 +164,8 @@ impl AggregateUDFImpl for SumDecimal {
     }
 
     fn is_nullable(&self) -> bool {
-        // SumDecimal is always nullable because overflows can cause null values
+        // In Spark, Sum.nullable and Average.nullable both return true irrespective of ANSI mode.
+        // SumDecimal is always nullable because overflows can cause null values.
         true
     }
 }
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 9426d1c848..be60f4aaee 100644
--- a/spark/src/test/scala/org/apache/comet/exec/CometAggregateSuite.scala
+++ b/spark/src/test/scala/org/apache/comet/exec/CometAggregateSuite.scala
@@ -1917,6 +1917,45 @@ class CometAggregateSuite extends CometTestBase with AdaptiveSparkPlanHelper {
     }
   }
 
+  test("SumDecimal and AvgDecimal nullable should always be true") {
+    // SumDecimal and AvgDecimal currently hardcode nullable=true.
+    // This matches Spark's Sum.nullable and Average.nullable which always return true,
+    // regardless of ANSI mode or input nullability.
+    val nonNullableData: Seq[(java.math.BigDecimal, Int)] = Seq(
+      (new java.math.BigDecimal("10.00"), 1),
+      (new java.math.BigDecimal("20.00"), 1),
+      (new java.math.BigDecimal("30.00"), 2))
+
+    val nullableData: Seq[(java.math.BigDecimal, Int)] = Seq(
+      (new java.math.BigDecimal("10.00"), 1),
+      (null.asInstanceOf[java.math.BigDecimal], 1),
+      (new java.math.BigDecimal("30.00"), 2))
+
+    Seq(true, false).foreach { ansiEnabled =>
+      withSQLConf(SQLConf.ANSI_ENABLED.key -> ansiEnabled.toString) {
+        withParquetTable(nonNullableData, "tbl") {
+          val sumRes = sql("SELECT _2, sum(_1) FROM tbl GROUP BY _2")
+          checkSparkAnswerAndOperator(sumRes)
+          assert(sumRes.schema.fields(1).nullable == true)
+
+          val avgRes = sql("SELECT _2, avg(_1) FROM tbl GROUP BY _2")
+          checkSparkAnswerAndOperator(avgRes)
+          assert(avgRes.schema.fields(1).nullable == true)
+        }
+
+        withParquetTable(nullableData, "tbl") {
+          val sumRes = sql("SELECT _2, sum(_1) FROM tbl GROUP BY _2")
+          checkSparkAnswerAndOperator(sumRes)
+          assert(sumRes.schema.fields(1).nullable == true)
+
+          val avgRes = sql("SELECT _2, avg(_1) FROM tbl GROUP BY _2")
+          checkSparkAnswerAndOperator(avgRes)
+          assert(avgRes.schema.fields(1).nullable == true)
+        }
+      }
+    }
+  }
+
   protected def checkSparkAnswerAndNumOfAggregates(query: String, numAggregates: Int): Unit = {
     val df = sql(query)
     checkSparkAnswer(df)