diff --git a/test/integration/api/test_main_api.py b/test/integration/api/test_main_api.py
index 4873bb5be3..a8ea407373 100644
--- a/test/integration/api/test_main_api.py
+++ b/test/integration/api/test_main_api.py
@@ -157,7 +157,12 @@ def data_with_binary_features_and_categorical_target():
 ])
 def test_api_predict_correct(task_type, metric_name):
     train_data, test_data, _ = get_dataset(task_type)
-    model = Fedot(problem=task_type, metric=[metric_name], **TESTS_MAIN_API_DEFAULT_PARAMS)
+    changed_api_params = {
+        **TESTS_MAIN_API_DEFAULT_PARAMS,
+        'timeout': 1,
+        'preset': 'fast_train'
+    }
+    model = Fedot(problem=task_type, metric=metric_name, **changed_api_params)
     fedot_model = model.fit(features=train_data)
     prediction = model.predict(features=test_data)
     metric = model.get_metrics(metric_names=metric_name, rounding_order=5)
diff --git a/test/integration/real_applications/test_examples.py b/test/integration/real_applications/test_examples.py
index dfb0a7d75e..7e25ef20ea 100644
--- a/test/integration/real_applications/test_examples.py
+++ b/test/integration/real_applications/test_examples.py
@@ -84,7 +84,7 @@ def test_api_example():
     prediction = run_classification_example(timeout=1, with_tuning=with_tuning)
     assert prediction is not None
 
-    forecast = run_ts_forecasting_example(dataset='australia', timeout=2, with_tuning=with_tuning)
+    forecast = run_ts_forecasting_example(dataset='australia', timeout=1, with_tuning=with_tuning)
     assert forecast is not None
 
     pareto = run_classification_multiobj_example(timeout=1, with_tuning=with_tuning)