diff --git a/nanobot/providers/azure_openai_provider.py b/nanobot/providers/azure_openai_provider.py
index b97743ab2..f2f63a5ba 100644
--- a/nanobot/providers/azure_openai_provider.py
+++ b/nanobot/providers/azure_openai_provider.py
@@ -160,13 +160,15 @@ class AzureOpenAIProvider(LLMProvider):
 
         try:
             stream = await self._client.responses.create(**body)
-            content, tool_calls, finish_reason = await consume_sdk_stream(
-                stream, on_content_delta,
+            content, tool_calls, finish_reason, usage, reasoning_content = (
+                await consume_sdk_stream(stream, on_content_delta)
             )
             return LLMResponse(
                 content=content or None,
                 tool_calls=tool_calls,
                 finish_reason=finish_reason,
+                usage=usage,
+                reasoning_content=reasoning_content,
             )
         except Exception as e:
             return self._handle_error(e)
diff --git a/nanobot/providers/openai_responses_common/parsing.py b/nanobot/providers/openai_responses_common/parsing.py
index 5de895534..df59babd5 100644
--- a/nanobot/providers/openai_responses_common/parsing.py
+++ b/nanobot/providers/openai_responses_common/parsing.py
@@ -122,6 +122,7 @@ def parse_response_output(response: Any) -> LLMResponse:
     output = response.get("output") or []
     content_parts: list[str] = []
     tool_calls: list[ToolCallRequest] = []
+    reasoning_content: str | None = None
 
     for item in output:
         if not isinstance(item, dict):
@@ -136,6 +137,14 @@ def parse_response_output(response: Any) -> LLMResponse:
                     block = dump() if callable(dump) else vars(block)
                 if block.get("type") == "output_text":
                     content_parts.append(block.get("text") or "")
+        elif item_type == "reasoning":
+            # Reasoning items may have a summary list with text blocks
+            for s in item.get("summary") or []:
+                if not isinstance(s, dict):
+                    dump = getattr(s, "model_dump", None)
+                    s = dump() if callable(dump) else vars(s)
+                if s.get("type") == "summary_text" and s.get("text"):
+                    reasoning_content = (reasoning_content or "") + s["text"]
         elif item_type == "function_call":
             call_id = item.get("call_id") or ""
             item_id = item.get("id") or "fc_0"
@@ -170,22 +179,26 @@ def parse_response_output(response: Any) -> LLMResponse:
         tool_calls=tool_calls,
         finish_reason=finish_reason,
         usage=usage,
+        reasoning_content=reasoning_content if isinstance(reasoning_content, str) else None,
     )
 
 
 async def consume_sdk_stream(
     stream: Any,
     on_content_delta: Callable[[str], Awaitable[None]] | None = None,
-) -> tuple[str, list[ToolCallRequest], str]:
+) -> tuple[str, list[ToolCallRequest], str, dict[str, int], str | None]:
     """Consume an SDK async stream from ``client.responses.create(stream=True)``.
 
     The SDK yields typed event objects with a ``.type`` attribute and
-    event-specific fields.  Returns ``(content, tool_calls, finish_reason)``.
+    event-specific fields.  Returns
+    ``(content, tool_calls, finish_reason, usage, reasoning_content)``.
     """
     content = ""
     tool_calls: list[ToolCallRequest] = []
     tool_call_buffers: dict[str, dict[str, Any]] = {}
     finish_reason = "stop"
+    usage: dict[str, int] = {}
+    reasoning_content: str | None = None
 
     async for event in stream:
         event_type = getattr(event, "type", None)
@@ -236,7 +249,24 @@ async def consume_sdk_stream(
             resp = getattr(event, "response", None)
             status = getattr(resp, "status", None) if resp else None
             finish_reason = map_finish_reason(status)
+            # Extract usage from the completed response
+            if resp:
+                usage_obj = getattr(resp, "usage", None)
+                if usage_obj:
+                    usage = {
+                        "prompt_tokens": int(getattr(usage_obj, "input_tokens", 0) or 0),
+                        "completion_tokens": int(getattr(usage_obj, "output_tokens", 0) or 0),
+                        "total_tokens": int(getattr(usage_obj, "total_tokens", 0) or 0),
+                    }
+                # Extract reasoning_content from completed output items
+                for out_item in getattr(resp, "output", None) or []:
+                    if getattr(out_item, "type", None) == "reasoning":
+                        for s in getattr(out_item, "summary", None) or []:
+                            if getattr(s, "type", None) == "summary_text":
+                                text = getattr(s, "text", None)
+                                if text:
+                                    reasoning_content = (reasoning_content or "") + text
         elif event_type in {"error", "response.failed"}:
             raise RuntimeError("Response failed")
 
-    return content, tool_calls, finish_reason
+    return content, tool_calls, finish_reason, usage, reasoning_content