diff --git a/litellm/llms/xai/chat/transformation.py b/litellm/llms/xai/chat/transformation.py
index 3161e3c968c..7325c0596a6 100644
--- a/litellm/llms/xai/chat/transformation.py
+++ b/litellm/llms/xai/chat/transformation.py
@@ -230,18 +230,53 @@ class XAIChatConfig(OpenAIGPTConfig):
         return response
 
     @staticmethod
-    def _fold_reasoning_tokens_into_completion(model_response: ModelResponse) -> None:
+    def _fold_reasoning_tokens_into_completion(
+        target: Union[ModelResponse, Usage, Dict[str, Any], None],
+    ) -> None:
         """Reconcile xAI Usage to the OpenAI invariant.
 
         xAI accounts ``reasoning_tokens`` separately from
         ``completion_tokens`` while still summing them into ``total_tokens``.
         OpenAI's contract (o1/o3) folds reasoning into ``completion_tokens``,
         so fold here to keep ``total = prompt + completion``. Idempotent.
+
+        Accepts a ``ModelResponse`` (non-streaming), a ``Usage`` object, or a
+        raw usage ``dict`` (streaming chunk) so streaming and non-streaming
+        paths stay in sync.
         """
-        usage = getattr(model_response, "usage", None)
+        if target is None:
+            return
+
+        if isinstance(target, ModelResponse):
+            usage: Union[Usage, Dict[str, Any], None] = getattr(target, "usage", None)
+        else:
+            usage = target
         if usage is None:
             return
 
+        if isinstance(usage, dict):
+            details = usage.get("completion_tokens_details") or {}
+            if isinstance(details, dict):
+                reasoning_tokens = int(details.get("reasoning_tokens") or 0)
+            else:
+                reasoning_tokens = int(getattr(details, "reasoning_tokens", 0) or 0)
+            if reasoning_tokens <= 0:
+                return
+
+            prompt_tokens = int(usage.get("prompt_tokens") or 0)
+            completion_tokens = int(usage.get("completion_tokens") or 0)
+            total_tokens = int(usage.get("total_tokens") or 0)
+
+            if total_tokens == prompt_tokens + completion_tokens:
+                return
+
+            # Guard against double-counting if xAI changes accounting.
+            if total_tokens != prompt_tokens + completion_tokens + reasoning_tokens:
+                return
+
+            usage["completion_tokens"] = completion_tokens + reasoning_tokens
+            return
+
         details = getattr(usage, "completion_tokens_details", None)
         reasoning_tokens = (
             int(getattr(details, "reasoning_tokens", 0) or 0) if details else 0
@@ -326,6 +361,7 @@ class XAIChatCompletionStreamingHandler(OpenAIChatCompletionStreamingHandler):
             chunk["choices"] = [{"index": 0, "delta": {}, "finish_reason": None}]
 
         if "usage" in chunk and chunk["usage"] is not None:
+            XAIChatConfig._fold_reasoning_tokens_into_completion(chunk["usage"])
             XAIChatConfig._normalize_openai_compatible_usage_totals(chunk["usage"])
 
         return super().chunk_parser(chunk)