diff --git a/litellm/constants.py b/litellm/constants.py
index 78aba30f9c0..765bbfe1e54 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -147,6 +147,7 @@ LITELLM_UI_ALLOW_HEADERS: Final = [
     "x-litellm-adaptive-router-model",
     "x-litellm-applied-guardrails",
     "x-litellm-guardrail-scan-id",
+    "x-litellm-cache-key",
 ]
 
 # Gemini model-specific minimal thinking budget constants
diff --git a/tests/test_litellm/proxy/test_proxy_server.py b/tests/test_litellm/proxy/test_proxy_server.py
index 3383527e932..b9a31acca96 100644
--- a/tests/test_litellm/proxy/test_proxy_server.py
+++ b/tests/test_litellm/proxy/test_proxy_server.py
@@ -78,6 +78,16 @@ def client_no_auth():
     return TestClient(app)
 
 
+def test_cors_exposes_cache_key_header_to_browser_js():
+    from fastapi.middleware.cors import CORSMiddleware
+
+    from litellm.constants import LITELLM_UI_ALLOW_HEADERS
+
+    cors_middleware = next(m for m in app.user_middleware if m.cls is CORSMiddleware)
+    assert cors_middleware.kwargs["expose_headers"] is LITELLM_UI_ALLOW_HEADERS
+    assert "x-litellm-cache-key" in cors_middleware.kwargs["expose_headers"]
+
+
 def test_login_v2_returns_redirect_url_and_sets_cookie(monkeypatch):
     mock_login_result = {"user_id": "test-user"}
     mock_prisma_client = MagicMock()
diff --git a/ui/litellm-dashboard/src/components/chat_ui/ResponseMetrics.test.tsx b/ui/litellm-dashboard/src/components/chat_ui/ResponseMetrics.test.tsx
index 5afc94eb043..f31e1839739 100644
--- a/ui/litellm-dashboard/src/components/chat_ui/ResponseMetrics.test.tsx
+++ b/ui/litellm-dashboard/src/components/chat_ui/ResponseMetrics.test.tsx
@@ -33,4 +33,22 @@ describe("ResponseMetrics prompt cache chips", () => {
     expect(screen.queryByText(/Cache Read/)).not.toBeInTheDocument();
     expect(screen.queryByText(/Cache Write/)).not.toBeInTheDocument();
   });
+
+  it("shows the response cache indicator instead of the provider cache chips on a response-cache hit", () => {
+    render(
+      <ResponseMetrics
+        usage={{ ...baseUsage, cacheReadTokens: 4695, cacheCreationTokens: 1234, servedFromResponseCache: true }}
+      />,
+    );
+
+    expect(screen.getByText("Response Cache: Hit")).toBeInTheDocument();
+    expect(screen.queryByText(/Cache Read/)).not.toBeInTheDocument();
+    expect(screen.queryByText(/Cache Write/)).not.toBeInTheDocument();
+  });
+
+  it("does not show the response cache indicator when the flag is absent", () => {
+    render(<ResponseMetrics usage={baseUsage} />);
+
+    expect(screen.queryByText(/Response Cache/)).not.toBeInTheDocument();
+  });
 });
diff --git a/ui/litellm-dashboard/src/components/chat_ui/ResponseMetrics.tsx b/ui/litellm-dashboard/src/components/chat_ui/ResponseMetrics.tsx
index 3e7f2884b23..ec62d0618d7 100644
--- a/ui/litellm-dashboard/src/components/chat_ui/ResponseMetrics.tsx
+++ b/ui/litellm-dashboard/src/components/chat_ui/ResponseMetrics.tsx
@@ -7,12 +7,16 @@ import {
   DatabaseBackup,
   DollarSign,
   Hash,
+  History,
   Lightbulb,
   Wrench,
 } from "lucide-react";
 import { Tooltip, TooltipContent, TooltipTrigger } from "@/components/ui/tooltip";
 import { PROMPT_CACHE_CREATION_TOOLTIP, PROMPT_CACHE_READ_TOOLTIP } from "@/utils/promptCacheUsage";
 
+const RESPONSE_CACHE_TOOLTIP =
+  "This response was replayed from LiteLLM's response cache. The request never reached the provider, so it did not read from or write to the provider's own prompt cache.";
+
 export interface TokenUsage {
   completionTokens?: number;
   promptTokens?: number;
@@ -21,6 +25,7 @@ export interface TokenUsage {
   cacheReadTokens?: number;
   cacheCreationTokens?: number;
   cost?: number;
+  servedFromResponseCache?: boolean;
 }
 
 interface ResponseMetricsProps {
@@ -51,7 +56,22 @@ function MetricItem({ label, tooltip, icon, value }: MetricItemProps) {
   );
 }
 
+function ResponseCacheIndicator() {
+  return (
+    <MetricItem
+      label="Response Cache"
+      tooltip={RESPONSE_CACHE_TOOLTIP}
+      icon={<History className="size-3" aria-hidden="true" />}
+      value="Hit"
+    />
+  );
+}
+
 function PromptCacheChips({ usage }: { usage?: TokenUsage }) {
+  if (usage?.servedFromResponseCache) {
+    return <ResponseCacheIndicator />;
+  }
+
   const readTokens = usage?.cacheReadTokens ?? 0;
   const creationTokens = usage?.cacheCreationTokens ?? 0;
 
diff --git a/ui/litellm-dashboard/src/components/llm_calls/chat_completion.test.tsx b/ui/litellm-dashboard/src/components/llm_calls/chat_completion.test.tsx
index c91de3f6b20..bc4b4e3a351 100644
--- a/ui/litellm-dashboard/src/components/llm_calls/chat_completion.test.tsx
+++ b/ui/litellm-dashboard/src/components/llm_calls/chat_completion.test.tsx
@@ -24,6 +24,10 @@ vi.mock("openai", () => ({
   },
 }));
 
+const nonStreamingResponse = (data: unknown, headers: Record<string, string> = {}) => ({
+  withResponse: async () => ({ data, response: { headers: new Headers(headers) } }),
+});
+
 describe("chat_completion", () => {
   const mockUpdateUI = vi.fn();
   const mockChatHistory = [{ role: "user", content: "Hello" }];
@@ -226,25 +230,27 @@ describe("chat_completion", () => {
   });
 
   it("should send a non-streaming request and render the whole message at once when streaming is disabled", async () => {
-    mockCreate.mockResolvedValueOnce({
-      id: "chatcmpl-1",
-      object: "chat.completion",
-      created: 1,
-      model: "gpt-4",
-      choices: [
-        {
-          index: 0,
-          finish_reason: "stop",
-          message: { role: "assistant", content: "Hello there" },
+    mockCreate.mockReturnValueOnce(
+      nonStreamingResponse({
+        id: "chatcmpl-1",
+        object: "chat.completion",
+        created: 1,
+        model: "gpt-4",
+        choices: [
+          {
+            index: 0,
+            finish_reason: "stop",
+            message: { role: "assistant", content: "Hello there" },
+          },
+        ],
+        usage: {
+          completion_tokens: 2,
+          prompt_tokens: 5,
+          total_tokens: 7,
+          cost: 0.25,
         },
-      ],
-      usage: {
-        completion_tokens: 2,
-        prompt_tokens: 5,
-        total_tokens: 7,
-        cost: 0.25,
-      },
-    });
+      }),
+    );
 
     const onTimingData = vi.fn();
     const onUsageData = vi.fn();
@@ -298,24 +304,26 @@ describe("chat_completion", () => {
   });
 
   it("should surface reasoning content and MCP metadata from a non-streaming response", async () => {
-    mockCreate.mockResolvedValueOnce({
-      model: "gpt-4",
-      choices: [
-        {
-          index: 0,
-          finish_reason: "stop",
-          message: {
-            role: "assistant",
-            content: "done",
-            reasoning_content: "thinking",
-            provider_specific_fields: {
-              mcp_tool_calls: [{ id: "call_1", function: { name: "search_docs", arguments: "{}" } }],
-              mcp_call_results: [{ tool_call_id: "call_1", result: "found it" }],
+    mockCreate.mockReturnValueOnce(
+      nonStreamingResponse({
+        model: "gpt-4",
+        choices: [
+          {
+            index: 0,
+            finish_reason: "stop",
+            message: {
+              role: "assistant",
+              content: "done",
+              reasoning_content: "thinking",
+              provider_specific_fields: {
+                mcp_tool_calls: [{ id: "call_1", function: { name: "search_docs", arguments: "{}" } }],
+                mcp_call_results: [{ tool_call_id: "call_1", result: "found it" }],
+              },
             },
           },
-        },
-      ],
-    });
+        ],
+      }),
+    );
 
     const onReasoningContent = vi.fn();
     const onMCPEvent = vi.fn();
@@ -459,3 +467,137 @@ describe("chat_completion prompt cache usage", () => {
     expect(usageData).not.toHaveProperty("cacheCreationTokens");
   });
 });
+
+describe("chat_completion response cache", () => {
+  const mockUpdateUI = vi.fn();
+  const mockChatHistory = [{ role: "user", content: "Hello" }];
+
+  afterEach(() => {
+    vi.clearAllMocks();
+  });
+
+  it("flags a non-streaming response-cache hit even though it replays provider prompt-cache usage", async () => {
+    mockCreate.mockReturnValueOnce(
+      nonStreamingResponse(
+        {
+          id: "chatcmpl-replayed",
+          model: "gpt-4",
+          choices: [{ index: 0, finish_reason: "stop", message: { role: "assistant", content: "Hello there" } }],
+          usage: {
+            completion_tokens: 2,
+            prompt_tokens: 5000,
+            total_tokens: 5002,
+            prompt_tokens_details: { cached_tokens: 4695 },
+          },
+        },
+        { "x-litellm-cache-key": "cache-key-abc" },
+      ),
+    );
+
+    const onUsageData = vi.fn();
+
+    await makeOpenAIChatCompletionRequest(
+      mockChatHistory,
+      mockUpdateUI,
+      "gpt-4",
+      "test-token",
+      undefined, // tags
+      undefined, // signal
+      undefined, // onReasoningContent
+      undefined, // onTimingData
+      onUsageData,
+      undefined, // traceId
+      undefined, // vector_store_ids
+      undefined, // guardrails
+      undefined, // policies
+      undefined, // selectedMCPServers
+      undefined, // onImageGenerated
+      undefined, // onSearchResults
+      undefined, // temperature
+      undefined, // max_tokens
+      undefined, // onTotalLatency
+      undefined, // customBaseUrl
+      undefined, // mcpServers
+      undefined, // mcpServerToolRestrictions
+      undefined, // onMCPEvent
+      undefined, // mockTestFallbacks
+      undefined, // mcpToolsets
+      false, // streamingEnabled
+    );
+
+    expect(onUsageData).toHaveBeenCalledWith(
+      expect.objectContaining({ cacheReadTokens: 4695, servedFromResponseCache: true }),
+    );
+  });
+
+  it("does not flag a non-streaming response that missed the response cache", async () => {
+    mockCreate.mockReturnValueOnce(
+      nonStreamingResponse({
+        id: "chatcmpl-fresh",
+        model: "gpt-4",
+        choices: [{ index: 0, finish_reason: "stop", message: { role: "assistant", content: "Hello there" } }],
+        usage: { completion_tokens: 2, prompt_tokens: 5, total_tokens: 7 },
+      }),
+    );
+
+    const onUsageData = vi.fn();
+
+    await makeOpenAIChatCompletionRequest(
+      mockChatHistory,
+      mockUpdateUI,
+      "gpt-4",
+      "test-token",
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      onUsageData,
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      false, // streamingEnabled
+    );
+
+    expect(onUsageData).toHaveBeenCalledWith(expect.not.objectContaining({ servedFromResponseCache: true }));
+  });
+
+  it("never flags a streaming response, even when the proxy reports a cache key", async () => {
+    async function* mockStream() {
+      yield {
+        choices: [{ delta: {}, index: 0 }],
+        model: "gpt-4",
+        usage: { completion_tokens: 2, prompt_tokens: 5, total_tokens: 7 },
+      };
+    }
+    mockCreate.mockResolvedValueOnce(mockStream());
+
+    const onUsageData = vi.fn();
+
+    await makeOpenAIChatCompletionRequest(
+      mockChatHistory,
+      mockUpdateUI,
+      "gpt-4",
+      "test-token",
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      onUsageData,
+    );
+
+    expect(onUsageData).toHaveBeenCalledWith(expect.not.objectContaining({ servedFromResponseCache: true }));
+  });
+});
diff --git a/ui/litellm-dashboard/src/components/llm_calls/chat_completion.tsx b/ui/litellm-dashboard/src/components/llm_calls/chat_completion.tsx
index ea66006349b..cd0852bc06e 100644
--- a/ui/litellm-dashboard/src/components/llm_calls/chat_completion.tsx
+++ b/ui/litellm-dashboard/src/components/llm_calls/chat_completion.tsx
@@ -73,6 +73,7 @@ export async function makeOpenAIChatCompletionRequest(
     const startTime = Date.now();
     let firstTokenReceived = false;
     let timeToFirstToken: number | undefined = undefined;
+    let servedFromResponseCache = false;
 
     // Track MCP metadata cumulatively across chunks
     let mcpMetadata: {
@@ -143,7 +144,13 @@ export async function makeOpenAIChatCompletionRequest(
           { ...requestBody, stream: true, stream_options: { include_usage: true } },
           { signal },
         )
-      : [completionAsSingleChunk(await client.chat.completions.create({ ...requestBody, stream: false }, { signal }))];
+      : await (async () => {
+          const nonStreamingResponse = await client.chat.completions
+            .create({ ...requestBody, stream: false }, { signal })
+            .withResponse();
+          servedFromResponseCache = nonStreamingResponse.response.headers.get("x-litellm-cache-key") !== null;
+          return [completionAsSingleChunk(nonStreamingResponse.data)];
+        })();
 
     for await (const chunk of response) {
       // Process content and measure time to first token
@@ -228,6 +235,7 @@ export async function makeOpenAIChatCompletionRequest(
           promptTokens: chunkWithUsage.usage.prompt_tokens,
           totalTokens: chunkWithUsage.usage.total_tokens,
           ...extractPromptCacheTokens(chunkWithUsage.usage),
+          ...(servedFromResponseCache ? { servedFromResponseCache: true } : {}),
         };
 
         // Check for reasoning tokens
diff --git a/ui/litellm-dashboard/src/components/llm_calls/responses_api.test.tsx b/ui/litellm-dashboard/src/components/llm_calls/responses_api.test.tsx
index 033813397fc..0b94c093acd 100644
--- a/ui/litellm-dashboard/src/components/llm_calls/responses_api.test.tsx
+++ b/ui/litellm-dashboard/src/components/llm_calls/responses_api.test.tsx
@@ -20,6 +20,10 @@ vi.mock("openai", () => ({
   },
 }));
 
+const nonStreamingResponse = (data: unknown, headers: Record<string, string> = {}) => ({
+  withResponse: async () => ({ data, response: { headers: new Headers(headers) } }),
+});
+
 describe("responses_api", () => {
   const mockUpdateTextUI = vi.fn();
   const messages: MessageType[] = [{ role: "user", content: "Hello" }];
@@ -71,19 +75,21 @@ describe("responses_api", () => {
   });
 
   it("should send a non-streaming request and render the whole output at once when streaming is disabled", async () => {
-    mockResponsesCreate.mockResolvedValueOnce({
-      id: "resp_456",
-      output: [
-        {
-          type: "message",
-          content: [
-            { type: "output_text", text: "Full " },
-            { type: "output_text", text: "answer" },
-          ],
-        },
-      ],
-      usage: { output_tokens: 3, input_tokens: 4, total_tokens: 7 },
-    });
+    mockResponsesCreate.mockReturnValueOnce(
+      nonStreamingResponse({
+        id: "resp_456",
+        output: [
+          {
+            type: "message",
+            content: [
+              { type: "output_text", text: "Full " },
+              { type: "output_text", text: "answer" },
+            ],
+          },
+        ],
+        usage: { output_tokens: 3, input_tokens: 4, total_tokens: 7 },
+      }),
+    );
 
     const onTimingData = vi.fn();
     const onUsageData = vi.fn();
@@ -162,10 +168,12 @@ describe("responses_api", () => {
     expect(onTotalLatency).toHaveBeenCalledTimes(1);
     expect(onTotalLatency).toHaveBeenLastCalledWith(expect.any(Number));
 
-    mockResponsesCreate.mockResolvedValueOnce({
-      id: "resp_latency",
-      output: [{ type: "message", content: [{ type: "output_text", text: "Answer" }] }],
-    });
+    mockResponsesCreate.mockReturnValueOnce(
+      nonStreamingResponse({
+        id: "resp_latency",
+        output: [{ type: "message", content: [{ type: "output_text", text: "Answer" }] }],
+      }),
+    );
 
     await callWithStreaming(false);
     expect(onTotalLatency).toHaveBeenCalledTimes(2);
@@ -224,14 +232,16 @@ describe("responses_api", () => {
   });
 
   it("should replay MCP output items as events for a non-streaming response", async () => {
-    mockResponsesCreate.mockResolvedValueOnce({
-      id: "resp_789",
-      output: [
-        { type: "mcp_call", id: "mcp_1", name: "search_docs", arguments: "{}", output: "found it" },
-        { type: "message", content: [{ type: "output_text", text: "Answer" }] },
-      ],
-      usage: { output_tokens: 1, input_tokens: 1, total_tokens: 2 },
-    });
+    mockResponsesCreate.mockReturnValueOnce(
+      nonStreamingResponse({
+        id: "resp_789",
+        output: [
+          { type: "mcp_call", id: "mcp_1", name: "search_docs", arguments: "{}", output: "found it" },
+          { type: "message", content: [{ type: "output_text", text: "Answer" }] },
+        ],
+        usage: { output_tokens: 1, input_tokens: 1, total_tokens: 2 },
+      }),
+    );
 
     const onMCPEvent = vi.fn();
     const onUsageData = vi.fn();
@@ -413,3 +423,131 @@ describe("responses_api prompt cache usage", () => {
     });
   });
 });
+
+describe("responses_api response cache", () => {
+  const mockUpdateTextUI = vi.fn();
+  const messages: MessageType[] = [{ role: "user", content: "Hello" }];
+
+  afterEach(() => {
+    vi.clearAllMocks();
+  });
+
+  it("flags a non-streaming response-cache hit even though it replays provider prompt-cache usage", async () => {
+    mockResponsesCreate.mockReturnValueOnce(
+      nonStreamingResponse(
+        {
+          id: "resp_replayed",
+          output: [{ type: "message", content: [{ type: "output_text", text: "Full answer" }] }],
+          usage: {
+            output_tokens: 2,
+            input_tokens: 5000,
+            total_tokens: 5002,
+            input_tokens_details: { cached_tokens: 4695 },
+          },
+        },
+        { "x-litellm-cache-key": "cache-key-abc" },
+      ),
+    );
+
+    const onUsageData = vi.fn();
+
+    await makeOpenAIResponsesRequest(
+      messages,
+      mockUpdateTextUI,
+      "gpt-4",
+      "test-token",
+      undefined, // tags
+      undefined, // signal
+      undefined, // onReasoningContent
+      undefined, // onTimingData
+      onUsageData,
+      undefined, // traceId
+      undefined, // vector_store_ids
+      undefined, // guardrails
+      undefined, // policies
+      undefined, // selectedMCPServers
+      undefined, // previousResponseId
+      undefined, // onResponseId
+      undefined, // onMCPEvent
+      undefined, // codeInterpreterEnabled
+      undefined, // onCodeInterpreterResult
+      undefined, // customBaseUrl
+      undefined, // mcpServers
+      undefined, // mcpServerToolRestrictions
+      undefined, // mcpToolsets
+      false, // streamingEnabled
+    );
+
+    expect(onUsageData).toHaveBeenCalledWith(
+      expect.objectContaining({ cacheReadTokens: 4695, servedFromResponseCache: true }),
+      "",
+    );
+  });
+
+  it("does not flag a non-streaming response that missed the response cache", async () => {
+    mockResponsesCreate.mockReturnValueOnce(
+      nonStreamingResponse({
+        id: "resp_fresh",
+        output: [{ type: "message", content: [{ type: "output_text", text: "Full answer" }] }],
+        usage: { output_tokens: 2, input_tokens: 5, total_tokens: 7 },
+      }),
+    );
+
+    const onUsageData = vi.fn();
+
+    await makeOpenAIResponsesRequest(
+      messages,
+      mockUpdateTextUI,
+      "gpt-4",
+      "test-token",
+      undefined, // tags
+      undefined, // signal
+      undefined, // onReasoningContent
+      undefined, // onTimingData
+      onUsageData,
+      undefined, // traceId
+      undefined, // vector_store_ids
+      undefined, // guardrails
+      undefined, // policies
+      undefined, // selectedMCPServers
+      undefined, // previousResponseId
+      undefined, // onResponseId
+      undefined, // onMCPEvent
+      undefined, // codeInterpreterEnabled
+      undefined, // onCodeInterpreterResult
+      undefined, // customBaseUrl
+      undefined, // mcpServers
+      undefined, // mcpServerToolRestrictions
+      undefined, // mcpToolsets
+      false, // streamingEnabled
+    );
+
+    expect(onUsageData).toHaveBeenCalledWith(expect.not.objectContaining({ servedFromResponseCache: true }), "");
+  });
+
+  it("never flags a streaming response, even when the proxy reports a cache key", async () => {
+    async function* mockStream() {
+      yield {
+        type: "response.completed",
+        response: { id: "resp_stream", usage: { output_tokens: 2, input_tokens: 5, total_tokens: 7 } },
+      };
+    }
+    mockResponsesCreate.mockResolvedValueOnce(mockStream());
+
+    const onUsageData = vi.fn();
+
+    await makeOpenAIResponsesRequest(
+      messages,
+      mockUpdateTextUI,
+      "gpt-4",
+      "test-token",
+      undefined,
+      undefined,
+      undefined,
+      undefined,
+      onUsageData,
+    );
+
+    expect(onUsageData).toHaveBeenCalledWith(expect.not.objectContaining({ servedFromResponseCache: true }), "");
+  });
+});
diff --git a/ui/litellm-dashboard/src/components/llm_calls/responses_api.tsx b/ui/litellm-dashboard/src/components/llm_calls/responses_api.tsx
index 8d71a4e29a8..7ab76488504 100644
--- a/ui/litellm-dashboard/src/components/llm_calls/responses_api.tsx
+++ b/ui/litellm-dashboard/src/components/llm_calls/responses_api.tsx
@@ -116,6 +116,7 @@ export async function makeOpenAIResponsesRequest(
   try {
     const startTime = Date.now();
     let firstTokenReceived = false;
+    let servedFromResponseCache = false;
 
     // Format messages for the API
     const formattedInput = messages.map((message) => {
@@ -202,7 +203,15 @@ export async function makeOpenAIResponsesRequest(
 
     // Create request to OpenAI responses API
     // Use 'any' type to avoid TypeScript issues with the experimental API
-    const response = await (client as any).responses.create({ ...requestBody, stream: streamingEnabled }, { signal });
+    const response = streamingEnabled
+      ? await (client as any).responses.create({ ...requestBody, stream: true }, { signal })
+      : await (async () => {
+          const nonStreamingResponse = await (client as any).responses
+            .create({ ...requestBody, stream: false }, { signal })
+            .withResponse();
+          servedFromResponseCache = nonStreamingResponse.response.headers.get("x-litellm-cache-key") !== null;
+          return nonStreamingResponse.data;
+        })();
     const events = streamingEnabled ? response : responseAsEvents(response);
 
     let mcpToolUsed = "";
@@ -292,6 +301,7 @@ export async function makeOpenAIResponsesRequest(
               promptTokens: usage.input_tokens,
               totalTokens: usage.total_tokens,
               ...extractPromptCacheTokens(usage),
+              ...(servedFromResponseCache ? { servedFromResponseCache: true } : {}),
             };
 
             // Add reasoning tokens if available