diff --git a/benchmark/mmmu/eval_utils.py b/benchmark/mmmu/eval_utils.py
index 1a358ab6c..d0ea42363 100644
--- a/benchmark/mmmu/eval_utils.py
+++ b/benchmark/mmmu/eval_utils.py
@@ -38,7 +38,7 @@ class EvalArgs:
     concurrency: int = 1
     max_new_tokens: Optional[int] = None
     temperature: Optional[float] = None
-    response_answer_regex: str = "(.*)"
+    response_answer_regex: str = "(?s)(.*)"
     lora_path: Optional[str] = None
     reasoning_effort: Optional[str] = None
 
@@ -273,11 +273,34 @@ def get_sampling_params(eval_args):
 
 
 # ----------- Process Multi-choice -------------
+def _parse_explicit_multi_choice_answer(response, all_choices):
+    choice_map = {choice.upper(): choice for choice in all_choices}
+    matches = []
+
+    answer_pattern = r"\banswer\s*:\s*\*{0,2}\s*\(?([A-Z])\)?\s*\*{0,2}(?![A-Za-z])"
+    for match in re.finditer(answer_pattern, response, flags=re.IGNORECASE):
+        candidate = match.group(1).upper()
+        if candidate in choice_map:
+            matches.append((match.start(1), choice_map[candidate]))
+
+    final_letter_pattern = r"(?:^|\n)\s*\*{0,2}\s*\(?([A-Z])\)?\s*\*{0,2}\s*\.?\s*$"
+    for match in re.finditer(final_letter_pattern, response, flags=re.IGNORECASE):
+        candidate = match.group(1).upper()
+        if candidate in choice_map:
+            matches.append((match.start(1), choice_map[candidate]))
+
+    return max(matches)[1] if matches else None
+
+
 def parse_multi_choice_response(response, all_choices, index2ans):
     """
     Parse the prediction from the generated response.
     Return the predicted index e.g., A, B, C, D.
     """
+    explicit_answer = _parse_explicit_multi_choice_answer(response, all_choices)
+    if explicit_answer is not None:
+        return explicit_answer
+
     for char in [",", ".", "!", "?", ";", ":", "'"]:
         response = response.strip(char)
     response = " " + response + " "  # add space to avoid partial match
diff --git a/test/registered/unit/bench/test_mmmu_eval_utils.py b/test/registered/unit/bench/test_mmmu_eval_utils.py
new file mode 100644
index 000000000..36f2bb695
--- /dev/null
+++ b/test/registered/unit/bench/test_mmmu_eval_utils.py
@@ -0,0 +1,183 @@
+import importlib.util
+import re
+import sys
+import types
+import unittest
+from pathlib import Path
+
+try:
+    from sglang.test.ci.ci_register import register_cpu_ci
+    from sglang.test.test_utils import CustomTestCase
+except ModuleNotFoundError:
+    CustomTestCase = unittest.TestCase
+
+    def register_cpu_ci(*args, **kwargs):
+        pass
+
+
+register_cpu_ci(est_time=5, suite="stage-a-test-cpu")
+
+
+def _load_mmmu_eval_utils():
+    repo_root = Path(__file__).resolve().parents[4]
+    module_path = repo_root / "benchmark" / "mmmu" / "eval_utils.py"
+    module_name = "_test_mmmu_eval_utils"
+
+    stub_modules = {
+        "data_utils": _build_data_utils_stub(),
+        "datasets": _build_datasets_stub(),
+        "numpy": _build_numpy_stub(),
+        "torch": types.ModuleType("torch"),
+        "tqdm": _build_tqdm_stub(),
+    }
+    previous_modules = {name: sys.modules.get(name) for name in stub_modules}
+    sys.modules.update(stub_modules)
+
+    spec = importlib.util.spec_from_file_location(module_name, module_path)
+    module = importlib.util.module_from_spec(spec)
+    sys.modules[module_name] = module
+    try:
+        spec.loader.exec_module(module)
+    finally:
+        for name, previous_module in previous_modules.items():
+            if previous_module is None:
+                sys.modules.pop(name, None)
+            else:
+                sys.modules[name] = previous_module
+
+    return module
+
+
+def _build_data_utils_stub():
+    module = types.ModuleType("data_utils")
+    module.CAT_SHORT2LONG = {}
+    module.DOMAIN_CAT2SUB_CAT = {}
+
+    def _unused(*args, **kwargs):
+        raise AssertionError("Unexpected data_utils call in MMMU parser unit test")
+
+    module.construct_prompt = _unused
+    module.load_yaml = _unused
+    module.process_single_sample = _unused
+    module.save_json = _unused
+    return module
+
+
+def _build_datasets_stub():
+    module = types.ModuleType("datasets")
+
+    def _unused(*args, **kwargs):
+        raise AssertionError("Unexpected datasets call in MMMU parser unit test")
+
+    module.concatenate_datasets = _unused
+    module.load_dataset = _unused
+    return module
+
+
+def _build_numpy_stub():
+    module = types.ModuleType("numpy")
+    module.argmax = lambda values: max(range(len(values)), key=values.__getitem__)
+    return module
+
+
+def _build_tqdm_stub():
+    module = types.ModuleType("tqdm")
+    module.tqdm = lambda iterable=None, *args, **kwargs: iterable
+    return module
+
+
+class TestMMMUEvalUtils(CustomTestCase):
+    @classmethod
+    def setUpClass(cls):
+        cls.eval_utils = _load_mmmu_eval_utils()
+
+    def test_default_response_answer_regex_captures_multiline_response(self):
+        response = "Based on the diagram, compare the labeled points.\nAnswer: B"
+
+        answer = re.search(self.eval_utils.EvalArgs.response_answer_regex, response)
+
+        self.assertIsNotNone(answer)
+        self.assertEqual(answer.group(1), response)
+
+    def test_default_regex_extraction_preserves_multiline_answer_for_processing(self):
+        response = "Based on the diagram, compare the labeled points.\nAnswer: B"
+        sample = self._multiple_choice_sample(response)
+        answer = re.search(self.eval_utils.EvalArgs.response_answer_regex, response)
+        answer_dict = {}
+        out_samples = {}
+        previous_random_choice = self.eval_utils.random.choice
+        self.eval_utils.random.choice = lambda choices: "A"
+        try:
+            self.eval_utils.process_result(
+                answer.group(1).strip() if answer else response,
+                sample,
+                answer_dict,
+                out_samples,
+            )
+        finally:
+            self.eval_utils.random.choice = previous_random_choice
+
+        self.assertEqual(out_samples["sample-1"]["pred_ans"], "B")
+
+    def test_parse_multi_choice_prefers_explicit_answer_marker_after_copied_options(
+        self,
+    ):
+        response = (
+            "The options are:\n"
+            "(A) red\n"
+            "(B) blue\n"
+            "(C) green\n"
+            "(D) yellow\n"
+            "Answer: B"
+        )
+
+        pred_ans = self.eval_utils.parse_multi_choice_response(
+            response, ["A", "B", "C", "D"], self._index_to_answer()
+        )
+
+        self.assertEqual(pred_ans, "B")
+
+    def test_parse_multi_choice_prefers_final_standalone_letter_after_copied_options(
+        self,
+    ):
+        response = (
+            "The options are:\n"
+            "(A) red\n"
+            "(B) blue\n"
+            "(C) green\n"
+            "(D) yellow\n"
+            "The diagram rules out the other labels.\n"
+            "**B**"
+        )
+
+        pred_ans = self.eval_utils.parse_multi_choice_response(
+            response, ["A", "B", "C", "D"], self._index_to_answer()
+        )
+
+        self.assertEqual(pred_ans, "B")
+
+    def test_parse_multi_choice_prefers_latest_explicit_answer(self):
+        response = "Initial thought: Answer: A\nAfter checking the image again:\n**B**"
+
+        pred_ans = self.eval_utils.parse_multi_choice_response(
+            response, ["A", "B", "C", "D"], self._index_to_answer()
+        )
+
+        self.assertEqual(pred_ans, "B")
+
+    def _multiple_choice_sample(self, response):
+        return {
+            "id": "sample-1",
+            "question_type": "multiple-choice",
+            "all_choices": ["A", "B", "C", "D"],
+            "index2ans": self._index_to_answer(),
+            "answer": "B",
+            "original_response": response,
+        }
+
+    def _index_to_answer(self):
+        return {"A": "red", "B": "blue", "C": "green", "D": "yellow"}
+
+
+if __name__ == "__main__":
+    unittest.main()