diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CacheLeakageCard.test.tsx b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CacheLeakageCard.test.tsx
index f320d8e0f97..126011723dd 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CacheLeakageCard.test.tsx
+++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/CacheLeakageCard.test.tsx
@@ -122,11 +122,11 @@ describe("CacheLeakageCard", () => {
     expect(firstDataRow()).toHaveTextContent("alpha");
   });
 
-  it("switches to the model view and lists only Anthropic models", () => {
+  it("switches to the model view and lists models from every provider", () => {
     renderWith([
       dayWithModels("2026-07-12", {
         "claude-sonnet-5": { prompt_tokens: 5000, cache_read_input_tokens: 0 },
-        "gpt-4o": { prompt_tokens: 8000, cache_read_input_tokens: 0 },
+        "vertex_ai/gemini-2.5-pro": { prompt_tokens: 8000, cache_read_input_tokens: 2000 },
       }),
     ]);
 
@@ -134,7 +134,7 @@ describe("CacheLeakageCard", () => {
 
     expect(screen.getByText("Cache leakage by model")).toBeInTheDocument();
     expect(screen.getByText("claude-sonnet-5")).toBeInTheDocument();
-    expect(screen.queryByText("gpt-4o")).not.toBeInTheDocument();
+    expect(screen.getByText("vertex_ai/gemini-2.5-pro")).toBeInTheDocument();
   });
 
   it("shows an empty state when no key used tokens in the range", () => {
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/costOptimizationUtils.test.ts b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/costOptimizationUtils.test.ts
index 5d2c48e6440..9c3915c812f 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/costOptimizationUtils.test.ts
+++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/costOptimizationUtils.test.ts
@@ -10,7 +10,6 @@ import {
   classificationRatePer1kTurns,
   computeCacheLeakage,
   formatRangeLabel,
-  isAnthropicModel,
   localIsoDay,
   savingsSeriesOf,
   toCumulative,
@@ -209,20 +208,21 @@ describe("computeCacheLeakage", () => {
 });
 
 describe("computeCacheLeakage by model", () => {
-  it("aggregates only Anthropic models and ignores other providers", () => {
+  it("lists every provider's models, not only Anthropic", () => {
     const models: Record<string, Partial<SpendMetrics>> = {
       "claude-sonnet-5": { prompt_tokens: 10000, cache_read_input_tokens: 0 },
-      "anthropic/claude-haiku-4-5": { prompt_tokens: 4000, cache_read_input_tokens: 0 },
-      "bedrock/anthropic.claude-3-5-sonnet": { prompt_tokens: 2000, cache_read_input_tokens: 0 },
-      "gpt-4o": { prompt_tokens: 9000, cache_read_input_tokens: 0 },
-      "deepseek-chat": { prompt_tokens: 8000, cache_read_input_tokens: 0 },
+      "vertex_ai/gemini-2.5-pro": { prompt_tokens: 9000, cache_read_input_tokens: 3000 },
+      "bedrock/openai.gpt-5.6-luna": { prompt_tokens: 8000, cache_read_input_tokens: 0 },
+      "deepseek-chat": { prompt_tokens: 4000, cache_read_input_tokens: 0 },
     };
     const { rows } = computeCacheLeakage([modelDay("2026-07-01", models)], "model");
     expect(rows.map((r) => r.id)).toEqual([
       "claude-sonnet-5",
-      "anthropic/claude-haiku-4-5",
-      "bedrock/anthropic.claude-3-5-sonnet",
+      "bedrock/openai.gpt-5.6-luna",
+      "vertex_ai/gemini-2.5-pro",
+      "deepseek-chat",
     ]);
+    expect(rows.find((r) => r.id === "vertex_ai/gemini-2.5-pro")?.cacheHitRatio).toBeCloseTo(1 / 3, 6);
   });
 
   it("labels model rows by model name with no sublabel", () => {
@@ -232,34 +232,20 @@ describe("computeCacheLeakage by model", () => {
     expect(rows[0].sublabel).toBeNull();
   });
 
-  it("prices model leakage at the Anthropic realized cache-read discount", () => {
+  it("prices model leakage at the realized cache-read discount across providers", () => {
     const results = [
       modelDay("2026-07-01", {
         "claude-sonnet-5": { prompt_tokens: 1000, cache_read_input_tokens: 1000, prompt_caching_savings_spend: 2.0 },
-        "claude-haiku-4-5": { prompt_tokens: 500 },
+        "gemini-2.5-flash": { prompt_tokens: 500 },
       }),
     ];
     const { rows, netSavingsPerCachedToken } = computeCacheLeakage(results, "model");
     expect(netSavingsPerCachedToken).toBeCloseTo(0.002, 6);
-    expect(rows.map((r) => r.id)).toEqual(["claude-haiku-4-5"]);
+    expect(rows.map((r) => r.id)).toEqual(["gemini-2.5-flash"]);
     expect(rows[0].potentialSavings).toBeCloseTo(1.0, 6);
   });
 });
 
-describe("isAnthropicModel", () => {
-  it("matches Claude-family models across providers and rejects others", () => {
-    const anthropic = [
-      "claude-sonnet-5",
-      "anthropic/claude-haiku-4-5",
-      "bedrock/anthropic.claude-3-5-sonnet",
-      "vertex_ai/claude-opus-4-8",
-    ];
-    const others = ["gpt-4o", "deepseek-chat", "gemini-2.5-pro", "mistral-large"];
-    expect(anthropic.every(isAnthropicModel)).toBe(true);
-    expect(others.some(isAnthropicModel)).toBe(false);
-  });
-});
-
 describe("buildDailyToolSeries", () => {
   const daily: ToolSpendDailyEntry[] = [
     { date: "2026-07-01", tool_name: "search", spend: 1.0, call_count: 1 },
diff --git a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/costOptimizationUtils.ts b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/costOptimizationUtils.ts
index 464c779aa2b..2e6d8208989 100644
--- a/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/costOptimizationUtils.ts
+++ b/ui/litellm-dashboard/src/app/(dashboard)/cost-optimization/_components/costOptimizationUtils.ts
@@ -44,8 +44,6 @@ export interface CacheLeakageResult {
   netSavingsPerCachedToken: number | null;
 }
 
-export const isAnthropicModel = (model: string): boolean => /claude|anthropic/i.test(model);
-
 interface LeakageAccumulator {
   alias: string | null;
   teamId: string | null;
@@ -96,7 +94,6 @@ const aggregateByModel = (results: readonly DailyData[]): Map<string, LeakageAcc
   const byModel = new Map<string, LeakageAccumulator>();
   for (const day of results) {
     for (const [model, entry] of Object.entries(day.breakdown?.models ?? {})) {
-      if (!isAnthropicModel(model)) continue;
       const acc = byModel.get(model) ?? emptyAccumulator();
       byModel.set(model, addMetrics(acc, entry.metrics, null, null));
     }