diff --git a/mlx_vlm/server.py b/mlx_vlm/server.py
index 04c011f6a..6f1a593f8 100644
--- a/mlx_vlm/server.py
+++ b/mlx_vlm/server.py
@@ -586,11 +586,14 @@ class GenerationRequest(VLMRequest):
     )
 
 
-class UsageStats(OpenAIUsage):
+class UsageStats(BaseModel):
     """
-    Inherits from OpenAIUsage and adds additional fields for usage statistics.
+    OpenAI chat-completion usage with extra MLX stats.
     """
 
+    prompt_tokens: int
+    completion_tokens: int
+    total_tokens: int
     prompt_tps: float = Field(..., description="Tokens per second for the prompt.")
     generation_tps: float = Field(
         ..., description="Tokens per second for the generation."
@@ -1142,8 +1145,8 @@ async def stream_generator():
 
                         # Yield chunks in Server-Sent Events (SSE) format
                         usage_stats = {
-                            "input_tokens": chunk.prompt_tokens,
-                            "output_tokens": chunk.generation_tokens,
+                            "prompt_tokens": chunk.prompt_tokens,
+                            "completion_tokens": chunk.generation_tokens,
                             "total_tokens": chunk.prompt_tokens
                             + chunk.generation_tokens,
                             "prompt_tps": chunk.prompt_tps,
@@ -1240,8 +1243,8 @@ async def stream_generator():
                 print("Generation finished, cleared cache.")
 
                 usage_stats = UsageStats(
-                    input_tokens=gen_result.prompt_tokens,
-                    output_tokens=gen_result.generation_tokens,
+                    prompt_tokens=gen_result.prompt_tokens,
+                    completion_tokens=gen_result.generation_tokens,
                     total_tokens=gen_result.total_tokens,
                     prompt_tps=gen_result.prompt_tps,
                     generation_tps=gen_result.generation_tps,
diff --git a/mlx_vlm/tests/test_server.py b/mlx_vlm/tests/test_server.py
index 270a82d77..2fdad7be9 100644
--- a/mlx_vlm/tests/test_server.py
+++ b/mlx_vlm/tests/test_server.py
@@ -130,3 +130,46 @@ def test_chat_completions_endpoint_forwards_explicit_sampling_args(client):
     assert mock_generate.call_args.kwargs["repetition_penalty"] == 1.15
     assert mock_generate.call_args.kwargs["logit_bias"] == {12: -1.5}
     assert mock_generate.call_args.kwargs["resize_shape"] == (512, 512)
+
+
+def test_chat_completions_response_uses_openai_usage_field_names(client):
+    """Regression: /chat/completions must return `prompt_tokens` /
+    `completion_tokens` / `total_tokens` per the OpenAI Chat Completions
+    spec, not the `/responses` API's `input_tokens` / `output_tokens`.
+    """
+    model = SimpleNamespace()
+    processor = SimpleNamespace()
+    config = SimpleNamespace(model_type="qwen2_vl")
+    result = SimpleNamespace(
+        text="done",
+        prompt_tokens=8,
+        generation_tokens=4,
+        total_tokens=12,
+        prompt_tps=10.0,
+        generation_tps=5.0,
+        peak_memory=0.1,
+    )
+
+    with (
+        patch.object(
+            server, "get_cached_model", return_value=(model, processor, config)
+        ),
+        patch.object(server, "apply_chat_template", return_value="prompt"),
+        patch.object(server, "generate", return_value=result),
+    ):
+        response = client.post(
+            "/chat/completions",
+            json={
+                "model": "demo",
+                "messages": [{"role": "user", "content": "Hello"}],
+                "max_tokens": 12,
+            },
+        )
+
+    assert response.status_code == 200
+    usage = response.json()["usage"]
+    assert usage["prompt_tokens"] == 8
+    assert usage["completion_tokens"] == 4
+    assert usage["total_tokens"] == 12
+    assert "input_tokens" not in usage
+    assert "output_tokens" not in usage