diff --git a/litellm/litellm_core_utils/streaming_handler.py b/litellm/litellm_core_utils/streaming_handler.py
index 128ba0bf3ab..b3288992854 100644
--- a/litellm/litellm_core_utils/streaming_handler.py
+++ b/litellm/litellm_core_utils/streaming_handler.py
@@ -39,6 +39,7 @@ from litellm.types.utils import (
 )
 from litellm.types.utils import GenericStreamingChunk as GChunk
 from litellm.types.utils import (
+    ChoiceLogprobs,
     LlmProviders,
     ModelResponse,
     ModelResponseStream,
@@ -1041,6 +1042,17 @@ class CustomStreamWrapper:
                 del model_response.choices[0].delta.reasoning_content
         return
 
+    @staticmethod
+    def _normalize_logprobs(logprobs: Any) -> Any:
+        """Convert raw provider/SDK logprobs into litellm's own ``ChoiceLogprobs`` so the chunk stays serializable."""
+        if logprobs is None or isinstance(logprobs, ChoiceLogprobs):
+            return logprobs
+        if isinstance(logprobs, BaseModel):
+            return ChoiceLogprobs(**logprobs.model_dump())
+        if isinstance(logprobs, dict):
+            return ChoiceLogprobs(**logprobs)
+        return logprobs
+
     def _dispatch_provider_chunk(
         self,
         chunk: Any,
@@ -1345,7 +1357,7 @@ class CustomStreamWrapper:
                     model_response.system_fingerprint = response_obj["original_chunk"].system_fingerprint
                     self.system_fingerprint = response_obj["original_chunk"].system_fingerprint
             if response_obj["logprobs"] is not None:
-                model_response.choices[0].logprobs = response_obj["logprobs"]
+                model_response.choices[0].logprobs = self._normalize_logprobs(response_obj["logprobs"])
 
             if response_obj["usage"] is not None:
                 if isinstance(response_obj["usage"], dict):
diff --git a/tests/test_litellm/litellm_core_utils/test_streaming_handler.py b/tests/test_litellm/litellm_core_utils/test_streaming_handler.py
index e430ce3b084..a0fd5516e24 100644
--- a/tests/test_litellm/litellm_core_utils/test_streaming_handler.py
+++ b/tests/test_litellm/litellm_core_utils/test_streaming_handler.py
@@ -22,6 +22,7 @@ from litellm.litellm_core_utils.streaming_handler import (
     _ProviderChunkParsed,
 )
 from litellm.types.utils import (
+    ChoiceLogprobs,
     CompletionTokensDetailsWrapper,
     Delta,
     ModelResponseStream,
@@ -3059,3 +3060,113 @@ async def test_stream_chunk_builder_raise_and_usage_recovery_failure_does_not_cr
             chunks = [c async for c in response]
 
     assert len(chunks) > 0
+
+
+def test_normalize_logprobs_converts_raw_sdk_object():
+    """
+    Regression test for https://github.com/BerriAI/litellm/issues/33456
+
+    openai SDK models are built with defer_build=True, so an instance parsed via
+    model_validate() (how the SDK parses every streaming chunk) keeps a MockValSer
+    placeholder serializer. If such a raw object is stored on a litellm chunk, a
+    later model_dump() blows up with
+    "'MockValSer' object cannot be converted to 'SchemaSerializer'".
+
+    _normalize_logprobs must convert it to litellm's own ChoiceLogprobs.
+    """
+    from openai.types.chat.chat_completion_chunk import (
+        ChoiceLogprobs as OpenAIChoiceLogprobs,
+    )
+
+    raw = OpenAIChoiceLogprobs.model_validate(
+        {
+            "content": [
+                {"token": "hi", "bytes": [104, 105], "logprob": -0.1, "top_logprobs": []}
+            ],
+            "refusal": None,
+        }
+    )
+
+    normalized = CustomStreamWrapper._normalize_logprobs(raw)
+
+    assert isinstance(normalized, ChoiceLogprobs)
+    assert type(normalized).__module__.startswith("litellm")
+    assert normalized.content is not None and normalized.content[0].token == "hi"
+
+    assert isinstance(
+        CustomStreamWrapper._normalize_logprobs({"content": None, "refusal": None}),
+        ChoiceLogprobs,
+    )
+    assert CustomStreamWrapper._normalize_logprobs(normalized) is normalized
+    assert CustomStreamWrapper._normalize_logprobs(None) is None
+
+
+@pytest.mark.asyncio
+async def test_streaming_logprobs_do_not_store_raw_sdk_object(logging_obj: Logging):
+    """
+    Regression test for https://github.com/BerriAI/litellm/issues/33456
+
+    A provider (e.g. SAP AI Core) that emits a final chunk carrying logprobs +
+    usage with an empty delta used to leave the raw openai SDK ChoiceLogprobs on
+    the litellm chunk. The subsequent model_dump() in __anext__ then crashed with
+    a MockValSer TypeError, which the router surfaced as MidStreamFallbackError and
+    truncated the stream mid-way.
+
+    The forwarded chunk's logprobs must be litellm's own ChoiceLogprobs and every
+    chunk must stay serializable via model_dump()/model_dump_json().
+    """
+    from litellm.types.llms.openai import OpenAIChatCompletionChunk
+
+    def _chunk(delta, finish=None, usage=None, logprobs=None):
+        payload = {
+            "id": "chatcmpl-33456",
+            "object": "chat.completion.chunk",
+            "created": 1,
+            "model": "gpt-4o",
+            "choices": [
+                {
+                    "index": 0,
+                    "delta": delta,
+                    "finish_reason": finish,
+                    "logprobs": logprobs,
+                }
+            ],
+        }
+        if usage is not None:
+            payload["usage"] = usage
+        return OpenAIChatCompletionChunk.model_validate(payload)
+
+    logprobs_payload = {
+        "content": [
+            {"token": "hi", "bytes": [104, 105], "logprob": -0.1, "top_logprobs": []}
+        ],
+        "refusal": None,
+    }
+
+    async def _stream():
+        yield _chunk({"role": "assistant", "content": "hi"})
+        yield _chunk(
+            {},
+            finish="stop",
+            logprobs=logprobs_payload,
+            usage={"prompt_tokens": 1, "completion_tokens": 1, "total_tokens": 2},
+        )
+
+    response = CustomStreamWrapper(
+        completion_stream=_stream(),
+        model="gpt-4o",
+        custom_llm_provider="openai",
+        logging_obj=logging_obj,
+    )
+
+    logprobs_chunks = []
+    async for chunk in response:
+        chunk.model_dump()
+        chunk.model_dump_json()
+        if chunk.choices and chunk.choices[0].logprobs is not None:
+            logprobs_chunks.append(chunk.choices[0].logprobs)
+
+    assert logprobs_chunks, "expected a forwarded chunk carrying logprobs"
+    for lp in logprobs_chunks:
+        assert isinstance(lp, ChoiceLogprobs)
+        assert "openai" not in type(lp).__module__