diff --git a/pkg/util/indexparamcheck/constraints.go b/pkg/util/indexparamcheck/constraints.go
index da778f3174..e368fbd378 100644
--- a/pkg/util/indexparamcheck/constraints.go
+++ b/pkg/util/indexparamcheck/constraints.go
@@ -20,10 +20,10 @@ const (
 	// DefaultMaxDim is the largest dimension supported in Milvus
 	DefaultMaxDim = 32768
 
-	// If Dim = 32 and raw vector data = 2G, query node need 24G disk space When loading the vectors' disk index
-	// If Dim = 2, and raw vector data = 2G, query node need 240G disk space When loading the vectors' disk index
-	// So DiskAnnMinDim should be greater than or equal to 32 to avoid running out of disk space
-	DiskAnnMinDim = 32
+	// If Dim = 32 and raw vector data = 2G, query node need ~17G disk space When loading the vectors' disk index
+	// If Dim = 2, and raw vector data = 2G, query node need ~60G disk space When loading the vectors' disk index
+	// So DiskAnnMinDim should be greater than or equal to 8 to avoid running out of disk space
+	DiskAnnMinDim = 8
 
 	HNSWMinEfConstruction = 8
 	HNSWMaxEfConstruction = 512
diff --git a/pkg/util/indexparamcheck/diskann_checker_test.go b/pkg/util/indexparamcheck/diskann_checker_test.go
index 2d228ad85b..374b5b33f2 100644
--- a/pkg/util/indexparamcheck/diskann_checker_test.go
+++ b/pkg/util/indexparamcheck/diskann_checker_test.go
@@ -23,7 +23,7 @@ func Test_diskannChecker_CheckTrain(t *testing.T) {
 	}
 
 	invalidParamsSmallDim := copyParams(validParams)
-	invalidParamsSmallDim[DIM] = strconv.Itoa(15)
+	invalidParamsSmallDim[DIM] = strconv.Itoa(4)
 
 	p1 := map[string]string{
 		DIM:    strconv.Itoa(128),
diff --git a/tests/python_client/testcases/test_index.py b/tests/python_client/testcases/test_index.py
index bfb55d52bc..775ba07723 100644
--- a/tests/python_client/testcases/test_index.py
+++ b/tests/python_client/testcases/test_index.py
@@ -1881,7 +1881,7 @@ class TestIndexDiskann(TestcaseBase):
             t.join()
 
     @pytest.mark.tags(CaseLabel.L1)
-    @pytest.mark.parametrize("dim", [1, 2, 8, 16, 24, 31])
+    @pytest.mark.parametrize("dim", [1, 2, 4, 6])
     def test_create_index_with_small_dim(self, dim):
         """
         target: test create index with diskann