diff --git a/apps/gateway/src/chat/chat.ts b/apps/gateway/src/chat/chat.ts
index 03f620a1d9..005b2244bc 100644
--- a/apps/gateway/src/chat/chat.ts
+++ b/apps/gateway/src/chat/chat.ts
@@ -2647,6 +2647,7 @@ chat.openapi(completions, async (c) => {
 					{
 						prompt: messages.map((m) => m.content).join("\n"),
 						completion: fullContent,
+						toolResults: streamingToolCalls || undefined,
 					},
 				);
 
@@ -3033,6 +3034,7 @@ chat.openapi(completions, async (c) => {
 		{
 			prompt: messages.map((m) => m.content).join("\n"),
 			completion: content,
+			toolResults: toolResults,
 		},
 	);
 
diff --git a/apps/gateway/src/lib/costs.spec.ts b/apps/gateway/src/lib/costs.spec.ts
index c4b365e8b0..4730ea4111 100644
--- a/apps/gateway/src/lib/costs.spec.ts
+++ b/apps/gateway/src/lib/costs.spec.ts
@@ -171,4 +171,83 @@ describe("calculateCosts", () => {
 
 		expect(result.discount).toBeUndefined(); // Should not include discount field when discount is 1
 	});
+
+	it("should calculate input costs even when output tokens are zero", () => {
+		const result = calculateCosts("gpt-4", "openai", 100, 0, null);
+
+		expect(result.inputCost).toBeCloseTo(0.001); // 100 * 0.00001
+		expect(result.outputCost).toBeCloseTo(0); // 0 * 0.00003
+		expect(result.totalCost).toBeCloseTo(0.001); // 0.001 + 0
+		expect(result.promptTokens).toBe(100);
+		expect(result.completionTokens).toBe(0);
+		expect(result.estimatedCost).toBe(false);
+	});
+
+	it("should calculate input costs when completion tokens are null but prompt tokens exist", () => {
+		const result = calculateCosts("gpt-4", "openai", 100, null, null);
+
+		expect(result.inputCost).toBeCloseTo(0.001); // 100 * 0.00001
+		expect(result.outputCost).toBeCloseTo(0); // 0 * 0.00003 (completion tokens set to 0)
+		expect(result.totalCost).toBeCloseTo(0.001); // 0.001 + 0
+		expect(result.promptTokens).toBe(100);
+		expect(result.completionTokens).toBe(0); // Should default to 0
+		expect(result.estimatedCost).toBe(false);
+	});
+
+	it("should include tool results in completion token estimation", () => {
+		const result = calculateCosts("gpt-4", "openai", null, null, null, {
+			prompt: "What's the weather like?",
+			completion: "", // Empty completion
+			toolResults: [
+				{
+					id: "call_1",
+					type: "function",
+					function: {
+						name: "get_weather",
+						arguments: '{"location": "San Francisco"}',
+					},
+				},
+				{
+					id: "call_2",
+					type: "function",
+					function: {
+						name: "get_temperature",
+						arguments: '{"location": "New York", "units": "celsius"}',
+					},
+				},
+			],
+		});
+
+		// Should calculate tokens for tool calls even with empty completion
+		expect(result.promptTokens).toBeGreaterThan(0);
+		expect(result.completionTokens).toBeGreaterThan(0); // Should include tool call tokens
+		expect(result.inputCost).toBeGreaterThan(0);
+		expect(result.outputCost).toBeGreaterThan(0); // Should have cost from tool calls
+		expect(result.totalCost).toBeGreaterThan(0);
+		expect(result.estimatedCost).toBe(true);
+	});
+
+	it("should handle tool results with missing function data gracefully", () => {
+		const result = calculateCosts("gpt-4", "openai", null, null, null, {
+			prompt: "What's the weather like?",
+			completion: "Here's the weather:",
+			toolResults: [
+				{ id: "call_1", type: "function" } as any, // Missing function data
+				{ id: "call_2", type: "function", function: {} as any }, // Missing name and arguments
+				{
+					id: "call_3",
+					type: "function",
+					function: {
+						name: "get_weather",
+						arguments: '{"location": "Paris"}',
+					},
+				},
+			],
+		});
+
+		// Should still work with partial tool result data
+		expect(result.promptTokens).toBeGreaterThan(0);
+		expect(result.completionTokens).toBeGreaterThan(0);
+		expect(result.estimatedCost).toBe(true);
+	});
 });
diff --git a/apps/gateway/src/lib/costs.ts b/apps/gateway/src/lib/costs.ts
index 8fbb6612f3..864db788fb 100644
--- a/apps/gateway/src/lib/costs.ts
+++ b/apps/gateway/src/lib/costs.ts
@@ -1,7 +1,12 @@
 import { encode, encodeChat } from "gpt-tokenizer";
 
 import { logger } from "@llmgateway/logger";
-import { type Model, type ModelDefinition, models } from "@llmgateway/models";
+import {
+	type Model,
+	type ModelDefinition,
+	models,
+	type ToolCall,
+} from "@llmgateway/models";
 
 // Define ChatMessage type to match what gpt-tokenizer expects
 interface ChatMessage {
@@ -27,6 +32,7 @@ export function calculateCosts(
 		messages?: ChatMessage[];
 		prompt?: string;
 		completion?: string;
+		toolResults?: ToolCall[];
 	},
 ) {
 	// Find the model info - try both base model name and provider model name
@@ -89,20 +95,39 @@ export function calculateCosts(
 		}
 
 		// Calculate completion tokens
-		if (!completionTokens && fullOutput && fullOutput.completion) {
-			try {
-				calculatedCompletionTokens = encode(
-					JSON.stringify(fullOutput.completion),
-				).length;
-			} catch (error) {
-				// If encoding fails, leave as null
-				logger.error(`Failed to encode completion text: ${error}`);
+		if (!completionTokens && fullOutput) {
+			let completionText = "";
+
+			// Include main completion content
+			if (fullOutput.completion) {
+				completionText += fullOutput.completion;
+			}
+
+			// Include tool results if available
+			if (fullOutput.toolResults && Array.isArray(fullOutput.toolResults)) {
+				for (const toolResult of fullOutput.toolResults) {
+					if (toolResult.function?.name) {
+						completionText += toolResult.function.name;
+					}
+					if (toolResult.function?.arguments) {
+						completionText += JSON.stringify(toolResult.function.arguments);
+					}
+				}
+			}
+
+			if (completionText) {
+				try {
+					calculatedCompletionTokens = encode(completionText).length;
+				} catch (error) {
+					// If encoding fails, leave as null
+					logger.error(`Failed to encode completion text: ${error}`);
+				}
 			}
 		}
 	}
 
-	// If we still don't have token counts, return null costs
-	if (!calculatedPromptTokens || !calculatedCompletionTokens) {
+	// If we don't have prompt tokens, we can't calculate any costs
+	if (!calculatedPromptTokens) {
 		return {
 			inputCost: null,
 			outputCost: null,
@@ -117,6 +142,11 @@ export function calculateCosts(
 		};
 	}
 
+	// Set completion tokens to 0 if not available (but still calculate input costs)
+	if (!calculatedCompletionTokens) {
+		calculatedCompletionTokens = 0;
+	}
+
 	// Find the provider-specific pricing
 	const providerInfo = modelInfo.providers.find(
 		(p) => p.providerId === provider,