diff --git a/tests/system/small/ml/test_llm.py b/tests/system/small/ml/test_llm.py
index 245fead028..999950007f 100644
--- a/tests/system/small/ml/test_llm.py
+++ b/tests/system/small/ml/test_llm.py
@@ -12,7 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from typing import Callable
+from contextlib import AbstractContextManager, nullcontext
+from typing import Any, Callable
 from unittest import mock
 
 import pandas as pd
@@ -25,6 +26,21 @@
 from bigframes.testing import utils
 
 
+@pytest.fixture(scope="function")
+def text_generator_model(request, bq_connection, session):
+    """Creates a text generator model, mocking creation for Claude models."""
+    model_class = request.param
+    if model_class == llm.Claude3TextGenerator:
+        # For Claude, mock the BQML model creation to avoid the network call
+        # that fails due to the region issue.
+        with mock.patch.object(llm.Claude3TextGenerator, "_create_bqml_model"):
+            model = model_class(connection_name=bq_connection, session=session)
+    else:
+        # For other models like Gemini, create as usual.
+        model = model_class(connection_name=bq_connection, session=session)
+    yield model
+
+
 @pytest.mark.parametrize(
     "model_name",
     ("text-embedding-005", "text-embedding-004", "text-multilingual-embedding-002"),
@@ -251,14 +267,10 @@ def __eq__(self, other):
         return self.equals(other)
 
 
-@pytest.mark.skip("b/436340035 test failed")
 @pytest.mark.parametrize(
-    (
-        "model_class",
-        "options",
-    ),
+    ("text_generator_model", "options"),
     [
-        (
+        pytest.param(
             llm.GeminiTextGenerator,
             {
                 "temperature": 0.9,
@@ -266,22 +278,24 @@ def __eq__(self, other):
                 "top_p": 1.0,
                 "ground_with_google_search": False,
             },
+            id="gemini",
         ),
-        (
+        pytest.param(
             llm.Claude3TextGenerator,
             {
                 "max_output_tokens": 128,
                 "top_k": 40,
                 "top_p": 0.95,
             },
+            id="claude",
         ),
     ],
+    indirect=["text_generator_model"],
 )
 def test_text_generator_retry_success(
     session,
-    model_class,
+    text_generator_model,
     options,
-    bq_connection,
 ):
     # Requests.
     df0 = EqCmpAllDataFrame(
@@ -298,21 +312,13 @@ def test_text_generator_retry_success(
     df1 = EqCmpAllDataFrame(
         {
             "ml_generate_text_status": ["error", "error"],
-            "prompt": [
-                "What is BQML?",
-                "What is BigQuery DataFrame?",
-            ],
+            "prompt": ["What is BQML?", "What is BigQuery DataFrame?"],
         },
         index=[1, 2],
         session=session,
     )
     df2 = EqCmpAllDataFrame(
-        {
-            "ml_generate_text_status": ["error"],
-            "prompt": [
-                "What is BQML?",
-            ],
-        },
+        {"ml_generate_text_status": ["error"], "prompt": ["What is BQML?"]},
         index=[1],
         session=session,
     )
@@ -342,31 +348,21 @@ def test_text_generator_retry_success(
         EqCmpAllDataFrame(
             {
                 "ml_generate_text_status": ["error", ""],
-                "prompt": [
-                    "What is BQML?",
-                    "What is BigQuery DataFrame?",
-                ],
+                "prompt": ["What is BQML?", "What is BigQuery DataFrame?"],
             },
             index=[1, 2],
             session=session,
         ),
         EqCmpAllDataFrame(
-            {
-                "ml_generate_text_status": [""],
-                "prompt": [
-                    "What is BQML?",
-                ],
-            },
+            {"ml_generate_text_status": [""], "prompt": ["What is BQML?"]},
             index=[1],
             session=session,
         ),
     ]
 
-    text_generator_model = model_class(connection_name=bq_connection, session=session)
     text_generator_model._bqml_model = mock_bqml_model
 
     with mock.patch.object(core.BqmlModel, "generate_text_tvf", generate_text_tvf):
-        # 3rd retry isn't triggered
         result = text_generator_model.predict(df0, max_retries=3)
 
         mock_generate_text.assert_has_calls(
@@ -391,17 +387,14 @@ def test_text_generator_retry_success(
             ),
             check_dtype=False,
             check_index_type=False,
+            check_like=True,
         )
 
 
-@pytest.mark.skip("b/436340035 test failed")
 @pytest.mark.parametrize(
-    (
-        "model_class",
-        "options",
-    ),
+    ("text_generator_model", "options"),
     [
-        (
+        pytest.param(
             llm.GeminiTextGenerator,
             {
                 "temperature": 0.9,
@@ -409,18 +402,21 @@ def test_text_generator_retry_success(
                 "top_p": 1.0,
                 "ground_with_google_search": False,
             },
+            id="gemini",
         ),
-        (
+        pytest.param(
             llm.Claude3TextGenerator,
             {
                 "max_output_tokens": 128,
                 "top_k": 40,
                 "top_p": 0.95,
             },
+            id="claude",
         ),
     ],
+    indirect=["text_generator_model"],
 )
-def test_text_generator_retry_no_progress(session, model_class, options, bq_connection):
+def test_text_generator_retry_no_progress(session, text_generator_model, options):
     # Requests.
     df0 = EqCmpAllDataFrame(
         {
@@ -480,7 +476,6 @@ def test_text_generator_retry_no_progress(session, model_class, options, bq_conn
         ),
     ]
 
-    text_generator_model = model_class(connection_name=bq_connection, session=session)
     text_generator_model._bqml_model = mock_bqml_model
 
     with mock.patch.object(core.BqmlModel, "generate_text_tvf", generate_text_tvf):
@@ -508,10 +503,10 @@ def test_text_generator_retry_no_progress(session, model_class, options, bq_conn
             ),
             check_dtype=False,
             check_index_type=False,
+            check_like=True,
         )
 
 
-@pytest.mark.skip("b/436340035 test failed")
 def test_text_embedding_generator_retry_success(session, bq_connection):
     # Requests.
     df0 = EqCmpAllDataFrame(
@@ -793,17 +788,28 @@ def test_gemini_preview_model_warnings(model_name):
         llm.GeminiTextGenerator(model_name=model_name)
 
 
-# b/436340035 temp disable the test to unblock presumbit
 @pytest.mark.parametrize(
     "model_class",
     [
         llm.TextEmbeddingGenerator,
         llm.MultimodalEmbeddingGenerator,
         llm.GeminiTextGenerator,
-        # llm.Claude3TextGenerator,
+        llm.Claude3TextGenerator,
     ],
 )
 def test_text_embedding_generator_no_default_model_warning(model_class):
     message = "Since upgrading the default model can cause unintended breakages, the\ndefault model will be removed in BigFrames 3.0. Please supply an\nexplicit model to avoid this message."
-    with pytest.warns(FutureWarning, match=message):
-        model_class(model_name=None)
+
+    # For Claude models, we must mock the model creation to avoid network errors.
+    # For all other models, we do nothing. contextlib.nullcontext() is a
+    # placeholder that allows the "with" statement to work for all cases.
+    patcher: AbstractContextManager[Any]
+    if model_class == llm.Claude3TextGenerator:
+        patcher = mock.patch.object(llm.Claude3TextGenerator, "_create_bqml_model")
+    else:
+        # We can now call nullcontext() directly
+        patcher = nullcontext()
+
+    with patcher:
+        with pytest.warns(FutureWarning, match=message):
+            model_class(model_name=None)