diff --git a/litellm/router.py b/litellm/router.py
index 24554e61516..5db79ff6fa2 100644
--- a/litellm/router.py
+++ b/litellm/router.py
@@ -686,9 +686,12 @@ class FallbackAwareAnthropicMessagesStream:
         existing_headers: Final = cast(  # cast-ok: additional_headers is always a dict[str, object] when present
             "dict[str, object]", self._hidden_params.get("additional_headers") or {}
         )
+        fallback_hidden_params_without_cost: Final = {
+            key: value for key, value in fallback_hidden_params.items() if key != "response_cost"
+        }
         self._hidden_params = {
             **self._hidden_params,
-            **fallback_hidden_params,
+            **fallback_hidden_params_without_cost,
             "additional_headers": dict(replace_complexity_router_headers(existing_headers, fallback_headers)),
         }
 
@@ -2874,9 +2877,14 @@ class Router:
         if not isinstance(item_headers, dict):
             item_headers = {}
 
+        # Streaming wrappers carry a placeholder response_cost (0.0) priced before any
+        # chunk arrives; the item's own value (None until usage lands) is the truthful one
+        fallback_hidden_params_without_cost: Final = {
+            key: value for key, value in fallback_hidden_params.items() if key != "response_cost"
+        }
         cast(_HiddenParamsHost, fallback_item)._hidden_params = {
             **item_hidden_params,
-            **fallback_hidden_params,
+            **fallback_hidden_params_without_cost,
             "additional_headers": {**item_headers, **fallback_headers},
         }
 
diff --git a/tests/unit/test_router_streaming_fallback_response_cost.py b/tests/unit/test_router_streaming_fallback_response_cost.py
new file mode 100644
index 00000000000..77671ce4087
--- /dev/null
+++ b/tests/unit/test_router_streaming_fallback_response_cost.py
@@ -0,0 +1,110 @@
+import json
+import threading
+from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
+from unittest.mock import MagicMock
+
+import pytest
+
+import litellm
+from litellm.router import Router
+
+
+def test_apply_fallback_hidden_params_keeps_chunk_response_cost():
+    chunk = litellm.ModelResponseStream(
+        id="test",
+        model="openai/internal-fallback",
+        choices=[],
+    )
+    chunk._hidden_params = {"response_cost": None, "model_id": "chunk-model-id"}
+    fallback_response = MagicMock()
+    fallback_response._hidden_params = {
+        "response_cost": 0.0,
+        "api_base": "https://fallback.example",
+    }
+
+    Router._apply_fallback_hidden_params_to_item(
+        fallback_item=chunk,
+        prepared_fallback_hidden_params=Router._prepare_fallback_hidden_params(fallback_response),
+    )
+
+    assert chunk._hidden_params["response_cost"] is None
+    assert chunk._hidden_params["api_base"] == "https://fallback.example"
+    assert chunk._hidden_params["model_id"] == "chunk-model-id"
+
+
+class _FakeOpenAI(BaseHTTPRequestHandler):
+    def log_message(self, *args):
+        pass
+
+    def do_POST(self):
+        group = self.path.strip("/").split("/")[0]
+        body = json.loads(self.rfile.read(int(self.headers["Content-Length"])))
+        self.send_response(200)
+        self.send_header("Content-Type", "text/event-stream")
+        self.end_headers()
+        if group == "primary-model":
+            error = {"error": {"message": "overloaded", "type": "server_error", "code": 500}}
+            self.wfile.write(f"data: {json.dumps(error)}\n\n".encode())
+        else:
+            base = {"id": "c", "object": "chat.completion.chunk", "created": 1, "model": body["model"]}
+            chunks = [
+                {
+                    **base,
+                    "choices": [{"index": 0, "delta": {"role": "assistant", "content": "Hi"}, "finish_reason": None}],
+                },
+                {**base, "choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}]},
+                {**base, "choices": [], "usage": {"prompt_tokens": 12, "completion_tokens": 12, "total_tokens": 24}},
+            ]
+            for chunk in chunks:
+                self.wfile.write(f"data: {json.dumps(chunk)}\n\n".encode())
+        self.wfile.write(b"data: [DONE]\n\n")
+
+
+@pytest.mark.asyncio
+async def test_streaming_fallback_chunks_carry_none_response_cost():
+    server = ThreadingHTTPServer(("127.0.0.1", 0), _FakeOpenAI)
+    threading.Thread(target=server.serve_forever, daemon=True).start()
+    root = f"http://127.0.0.1:{server.server_address[1]}"
+
+    router = litellm.Router(
+        model_list=[
+            {
+                "model_name": "primary-model",
+                "litellm_params": {
+                    "model": "openai/gpt-4o-mini",
+                    "api_key": "sk-fake",
+                    "api_base": f"{root}/primary-model/v1",
+                },
+            },
+            {
+                "model_name": "fallback-model",
+                "litellm_params": {
+                    "model": "openai/gpt-4o",
+                    "api_key": "sk-fake",
+                    "api_base": f"{root}/fallback-model/v1",
+                },
+            },
+        ],
+        fallbacks=[{"primary-model": ["fallback-model"]}],
+        num_retries=0,
+    )
+
+    stream = await router.acompletion(
+        model="primary-model",
+        messages=[{"role": "user", "content": "hi"}],
+        stream=True,
+        stream_options={"include_usage": True},
+    )
+    chunk_costs = []
+    usage_costs = []
+    async for chunk in stream:
+        chunk_costs.append(chunk._hidden_params.get("response_cost"))
+        usage = getattr(chunk, "usage", None)
+        if usage is not None:
+            usage_costs.append(getattr(usage, "cost", None))
+    server.shutdown()
+
+    assert len(chunk_costs) > 0
+    assert chunk_costs == [None] * len(chunk_costs)
+    assert len(usage_costs) > 0
+    assert usage_costs[-1] is not None and usage_costs[-1] > 0