diff --git a/litellm/responses/main.py b/litellm/responses/main.py
index 12f9be970c7..453676937fc 100644
--- a/litellm/responses/main.py
+++ b/litellm/responses/main.py
@@ -494,7 +494,14 @@ async def aresponses(
                 prompt_label=kwargs.get("prompt_label", None),
                 prompt_version=kwargs.get("prompt_version", None),
             )
-            input = cast(Union[str, ResponseInputParam], merged_input)
+            input = cast(
+                Union[str, ResponseInputParam],
+                ResponsesAPIRequestUtils.merge_prompt_management_input(
+                    original_input=input,
+                    client_input=client_input,
+                    merged_input=merged_input,
+                ),
+            )
             if model != original_model:
                 _, custom_llm_provider, _, _ = litellm.get_llm_provider(model=model)
             kwargs.pop("prompt_id", None)
@@ -609,7 +616,14 @@ def _apply_prompt_management_to_responses_call(
             prompt_label=kwargs.get("prompt_label", None),
             prompt_version=kwargs.get("prompt_version", None),
         )
-        input = cast(Union[str, ResponseInputParam], merged_input)
+        input = cast(
+            Union[str, ResponseInputParam],
+            ResponsesAPIRequestUtils.merge_prompt_management_input(
+                original_input=input,
+                client_input=client_input,
+                merged_input=merged_input,
+            ),
+        )
         local_vars["input"] = input
         local_vars["model"] = model
         if model != original_model:
diff --git a/litellm/responses/utils.py b/litellm/responses/utils.py
index 234eb777aca..6d42e33a268 100644
--- a/litellm/responses/utils.py
+++ b/litellm/responses/utils.py
@@ -19,7 +19,9 @@ import litellm
 from litellm._logging import verbose_logger
 from litellm.llms.base_llm.responses.transformation import BaseResponsesAPIConfig
 from litellm.types.llms.openai import (
+    AllMessageValues,
     ResponseAPIUsage,
+    ResponseInputParam,
     ResponsesAPIOptionalRequestParams,
     ResponsesAPIResponse,
     ResponseText,
@@ -36,6 +38,54 @@ from litellm.types.utils import (
 class ResponsesAPIRequestUtils:
     """Helper utils for constructing ResponseAPI requests"""
 
+    @staticmethod
+    def merge_prompt_management_input(
+        original_input: str | ResponseInputParam,
+        client_input: list[AllMessageValues],
+        merged_input: list[AllMessageValues],
+    ) -> list[object]:
+        if isinstance(original_input, str):
+            return [*merged_input]
+
+        original_items = tuple(original_input)
+        client_item_ids = frozenset(id(item) for item in client_input)
+        message_positions = tuple(index for index, item in enumerate(original_items) if id(item) in client_item_ids)
+
+        if len(message_positions) == len(original_items):
+            return [*merged_input]
+        if not message_positions:
+            return [*merged_input, *original_items]
+
+        corresponding_messages = len(client_input) == len(merged_input) and all(
+            original.get("role") == merged.get("role")
+            and (not isinstance(original.get("id"), str) or original.get("id") == merged.get("id"))
+            for original, merged in zip(client_input, merged_input)
+        )
+        if corresponding_messages:
+            merged_by_position = dict(zip(message_positions, merged_input))
+            return [
+                merged_by_position[index] if index in merged_by_position else item
+                for index, item in enumerate(original_items)
+            ]
+
+        all_messages_preserved = all(any(original is merged for merged in merged_input) for original in client_input)
+        if all_messages_preserved:
+            prefixes = {
+                id(original_items[position]): original_items[
+                    message_positions[index - 1] + 1 if index else 0 : position
+                ]
+                for index, position in enumerate(message_positions)
+            }
+            trailing_items = original_items[message_positions[-1] + 1 :]
+            return [item for merged in merged_input for item in (*prefixes.get(id(merged), ()), merged)] + list(
+                trailing_items
+            )
+
+        verbose_logger.warning(
+            "Prompt management hook replaced Responses API messages; non-message input items were dropped"
+        )
+        return [*merged_input]
+
     @staticmethod
     def _check_valid_arg(
         supported_params: Optional[List[str]],
diff --git a/tests/test_litellm/responses/test_responses_prompt_management.py b/tests/test_litellm/responses/test_responses_prompt_management.py
index 84e98390268..e4207b292da 100644
--- a/tests/test_litellm/responses/test_responses_prompt_management.py
+++ b/tests/test_litellm/responses/test_responses_prompt_management.py
@@ -14,13 +14,19 @@ Covers:
 """
 
 import asyncio
-from typing import List
+from typing import List, cast
 from unittest.mock import AsyncMock, MagicMock, patch
 
 import pytest
 
+from litellm.integrations.anthropic_cache_control_hook import (
+    AnthropicCacheControlHook,
+)
 from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
-from litellm.types.llms.openai import AllMessageValues
+from litellm.types.llms.openai import (
+    AllMessageValues,
+    ResponseInputParam,
+)
 
 # ---------------------------------------------------------------------------
 # Helpers
@@ -54,18 +60,15 @@ def _patch_responses_dispatch():
             return_value=("gpt-4o", "openai", None, None),
         ),
         patch(
-            "litellm.responses.mcp.litellm_proxy_mcp_handler."
-            "LiteLLM_Proxy_MCP_Handler._should_use_litellm_mcp_gateway",
+            "litellm.responses.mcp.litellm_proxy_mcp_handler.LiteLLM_Proxy_MCP_Handler._should_use_litellm_mcp_gateway",
             return_value=False,
         ),
         patch(
-            "litellm.responses.main.ProviderConfigManager"
-            ".get_provider_responses_api_config",
+            "litellm.responses.main.ProviderConfigManager.get_provider_responses_api_config",
             return_value=None,
         ),
         patch(
-            "litellm.responses.main.litellm_completion_transformation_handler"
-            ".response_api_handler",
+            "litellm.responses.main.litellm_completion_transformation_handler.response_api_handler",
             return_value=MagicMock(),
         ),
     ]
@@ -77,7 +80,6 @@ def _patch_responses_dispatch():
 
 
 class TestResponsesAPIPromptManagement:
-
     def test_str_input_coerced_and_merged(self):
         """[A] str input is wrapped into a message list before being passed to the hook."""
         template_messages: List[AllMessageValues] = [
@@ -108,9 +110,7 @@ class TestResponsesAPIPromptManagement:
         logging_obj.get_chat_completion_prompt.assert_called_once()
         call_kwargs = logging_obj.get_chat_completion_prompt.call_args.kwargs
         # str was coerced to a single user message before being passed to the hook
-        assert call_kwargs["messages"] == [
-            {"role": "user", "content": "Tell me about AI."}
-        ]
+        assert call_kwargs["messages"] == [{"role": "user", "content": "Tell me about AI."}]
         assert call_kwargs["prompt_id"] == "summariser-prompt"
 
     def test_list_input_merged_with_template(self):
@@ -256,6 +256,76 @@ class TestResponsesAPIPromptManagement:
         assert all(isinstance(m, dict) and "role" in m for m in passed_messages)
         assert len(passed_messages) == 1
 
+    def test_cache_control_hook_preserves_reasoning_items(self):
+        system_message = cast(
+            AllMessageValues,
+            {"role": "system", "content": "Analyze the request"},
+        )
+        assistant_message = cast(
+            AllMessageValues,
+            {
+                "type": "message",
+                "id": "msg_1",
+                "role": "assistant",
+                "status": "completed",
+                "content": [
+                    {
+                        "type": "output_text",
+                        "text": "The code has a bug",
+                        "annotations": [],
+                    }
+                ],
+            },
+        )
+        user_message = cast(
+            AllMessageValues,
+            {"role": "user", "content": "Check for security issues"},
+        )
+        reasoning_item = {
+            "type": "reasoning",
+            "id": "rs_1",
+            "summary": [],
+            "encrypted_content": "encrypted",
+        }
+        original_input = cast(
+            ResponseInputParam,
+            [system_message, reasoning_item, assistant_message, user_message],
+        )
+        _, merged_messages, _ = AnthropicCacheControlHook().get_chat_completion_prompt(
+            model="azure/gpt-5-codex",
+            messages=[system_message, assistant_message, user_message],
+            non_default_params={"cache_control_injection_points": [{"location": "message", "role": "system"}]},
+            prompt_id=None,
+            prompt_variables=None,
+            dynamic_callback_params={},
+        )
+        logging_obj = _make_logging_obj(
+            merged_model="azure/gpt-5-codex",
+            merged_messages=merged_messages,
+        )
+
+        patches = _patch_responses_dispatch()
+        with patches[0], patches[1], patches[2], patches[3] as mock_handler:
+            import litellm
+
+            litellm.responses(
+                input=original_input,
+                model="azure/gpt-5-codex",
+                litellm_logging_obj=logging_obj,
+                cache_control_injection_points=[{"location": "message", "role": "system"}],
+            )
+
+        sent_input = mock_handler.call_args.kwargs["input"]
+        assert [item.get("type") for item in sent_input] == [
+            None,
+            "reasoning",
+            "message",
+            None,
+        ]
+        assert sent_input[0]["cache_control"] == {"type": "ephemeral"}
+        assert sent_input[1] == reasoning_item
+        assert sent_input[2]["id"] == "msg_1"
+
     def test_model_override_re_resolves_provider(self):
         """[G] When the prompt template overrides the model to a different provider,
         custom_llm_provider is re-resolved so downstream routing uses the correct provider.