diff --git a/test/registered/openai_server/basic/test_serving_transcription.py b/test/registered/openai_server/basic/test_serving_transcription.py
new file mode 100644
index 000000000..6a51d36a7
--- /dev/null
+++ b/test/registered/openai_server/basic/test_serving_transcription.py
@@ -0,0 +1,108 @@
+"""
+Test the OpenAI-compatible /v1/audio/transcriptions endpoint with Whisper.
+
+Usage:
+    python3 test_serving_transcription.py -v
+"""
+
+import io
+import unittest
+
+import requests
+
+from sglang.srt.utils import kill_process_tree
+from sglang.test.ci.ci_register import register_cuda_ci
+from sglang.test.test_utils import (
+    DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+    DEFAULT_URL_FOR_TEST,
+    CustomTestCase,
+    popen_launch_server,
+)
+
+register_cuda_ci(est_time=120, suite="stage-b-test-1-gpu-small")
+
+WHISPER_MODEL = "openai/whisper-large-v3"
+AUDIO_URL = "https://raw.githubusercontent.com/sgl-project/sgl-test-files/refs/heads/main/audios/Trump_WEF_2018_10s.mp3"
+
+
+def download_audio_bytes(url=AUDIO_URL):
+    """Download audio file and return raw bytes."""
+    response = requests.get(url, timeout=30)
+    response.raise_for_status()
+    return response.content
+
+
+class TestServingTranscription(CustomTestCase):
+    """Test Whisper transcription via /v1/audio/transcriptions endpoint."""
+
+    @classmethod
+    def setUpClass(cls):
+        cls.model = WHISPER_MODEL
+        cls.base_url = DEFAULT_URL_FOR_TEST
+        cls.process = popen_launch_server(
+            cls.model,
+            cls.base_url,
+            timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
+            other_args=[
+                "--served-model-name",
+                "whisper",
+            ],
+        )
+
+    @classmethod
+    def tearDownClass(cls):
+        if hasattr(cls, "process") and cls.process:
+            kill_process_tree(cls.process.pid)
+
+    def _transcribe(self, language="en"):
+        """Send a transcription request and return the JSON response."""
+        audio_bytes = download_audio_bytes()
+        response = requests.post(
+            self.base_url + "/v1/audio/transcriptions",
+            files={"file": ("audio.mp3", io.BytesIO(audio_bytes), "audio/mpeg")},
+            data={
+                "model": "whisper",
+                "language": language,
+            },
+        )
+        self.assertEqual(response.status_code, 200, response.text)
+        return response.json()
+
+    def test_basic_transcription(self):
+        """Test that transcription returns a valid non-empty response."""
+        result = self._transcribe()
+        self.assertIn("text", result)
+        self.assertTrue(len(result["text"]) > 0, "Transcription should not be empty")
+
+    def test_transcription_content_quality(self):
+        """Test that transcription captures key content from the audio."""
+        result = self._transcribe()
+        text = result["text"].lower()
+        keywords = ["privilege", "leader", "science", "art"]
+        matches = [kw for kw in keywords if kw in text]
+        self.assertGreaterEqual(
+            len(matches),
+            2,
+            f"Expected at least 2 of {keywords} in transcription, "
+            f"found {matches}. Full text: {text}",
+        )
+
+    def test_multiple_sequential_requests(self):
+        """Test that sequential requests produce consistent results."""
+        results = []
+        for _ in range(3):
+            result = self._transcribe()
+            self.assertIn("text", result)
+            self.assertTrue(len(result["text"]) > 0)
+            results.append(result["text"])
+
+        for i in range(1, len(results)):
+            self.assertEqual(
+                results[0],
+                results[i],
+                f"Transcription {i + 1} differs from first transcription",
+            )
+
+
+if __name__ == "__main__":
+    unittest.main()