diff --git a/litellm/llms/base_llm/passthrough/transformation.py b/litellm/llms/base_llm/passthrough/transformation.py
index 34533e4c603..d97ecddc75d 100644
--- a/litellm/llms/base_llm/passthrough/transformation.py
+++ b/litellm/llms/base_llm/passthrough/transformation.py
@@ -8,11 +8,27 @@ if TYPE_CHECKING:
     from httpx import URL, Headers, Response
 
     from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
-    from litellm.types.utils import CostResponseTypes
+    from litellm.types.utils import CostResponseTypes, StandardPassThroughResponseObject
 
     from ..chat.transformation import BaseLLMException
 
 
+def strip_leading_model_segment(endpoint: str, model_names: tuple[str, ...]) -> str:
+    path: Final = endpoint.lstrip("/")
+    for model_name in model_names:
+        if not model_name:
+            continue
+        if path == model_name:
+            return ""
+        if path.startswith(f"{model_name}/"):
+            return path[len(model_name) + 1 :]
+    return path
+
+
+def replace_path_segment(endpoint: str, segment: str, replacement: str) -> str:
+    return "/".join(replacement if part == segment else part for part in endpoint.split("/"))
+
+
 class BasePassthroughConfig(BaseLLMModelInfo):
     @abstractmethod
     def is_streaming_request(self, endpoint: str, request_data: dict) -> bool:
@@ -104,7 +120,7 @@ class BasePassthroughConfig(BaseLLMModelInfo):
         request_data: dict,
         logging_obj: "LiteLLMLoggingObj",
         endpoint: str,
-    ) -> Optional["CostResponseTypes"]:
+    ) -> Optional["CostResponseTypes | StandardPassThroughResponseObject"]:
         pass
 
     def handle_logging_collected_chunks(
diff --git a/litellm/router.py b/litellm/router.py
index 9b7a7ee7ce8..273c1f9d99c 100644
--- a/litellm/router.py
+++ b/litellm/router.py
@@ -86,6 +86,7 @@ from litellm.litellm_core_utils.sensitive_data_masker import (
     mask_credentials_in_payload,
     mask_sensitive_structure,
 )
+from litellm.llms.base_llm.passthrough.transformation import replace_path_segment
 from litellm.llms.base_llm.vector_store.transformation import (
     RouterVectorStoreEmbeddingExecutor,
     vector_store_request_metadata,
@@ -5010,7 +5011,7 @@ class Router:
                 # If get_llm_provider fails, fall back to using model_name as-is
                 replacement_model_name = model_name
 
-            kwargs["endpoint"] = kwargs["endpoint"].replace(model, replacement_model_name)
+            kwargs["endpoint"] = replace_path_segment(kwargs["endpoint"], model, replacement_model_name)
         return kwargs
 
     async def _ageneric_api_call_with_fallbacks_helper(self, model: str, original_generic_function: Callable, **kwargs):
diff --git a/tests/test_litellm/test_router.py b/tests/test_litellm/test_router.py
index b220b23c338..0f4e199694d 100644
--- a/tests/test_litellm/test_router.py
+++ b/tests/test_litellm/test_router.py
@@ -4469,6 +4469,29 @@ def test_get_deployment_model_info_base_model_merge_priority():
     print("✓ Base model merge priority test passed!")
 
 
+def test_add_deployment_model_to_endpoint_rewrites_whole_path_segments_only():
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "gpt",
+                "litellm_params": {
+                    "model": "azure_ai/gpt-5.4-mini",
+                    "api_base": "https://my-resource.services.ai.azure.com",
+                    "api_key": "key",
+                },
+            }
+        ],
+    )
+
+    result = router._add_deployment_model_to_endpoint_for_llm_passthrough_route(
+        kwargs={"endpoint": "gpt/openai/deployments/gpt-4o/chat/completions", "custom_llm_provider": "azure_ai"},
+        model="gpt",
+        model_name="azure_ai/gpt-5.4-mini",
+    )
+
+    assert result["endpoint"] == "gpt-5.4-mini/openai/deployments/gpt-4o/chat/completions"
+
+
 def test_add_deployment_model_to_endpoint_for_llm_passthrough_route():
     """
     Test that _add_deployment_model_to_endpoint_for_llm_passthrough_route correctly strips bedrock provider prefix