diff --git a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/models.ipynb b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/models.ipynb
index 8674b4195..cf719e10d 100644
--- a/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/models.ipynb
+++ b/python/packages/autogen-core/docs/src/user-guide/agentchat-user-guide/tutorial/models.ipynb
@@ -373,6 +373,7 @@
     "```{note}\n",
     "While some model providers may offer OpenAI-compatible APIs, they may still have minor differences.\n",
     "For example, the `finish_reason` field may be different in the response.\n",
+    "\n",
     "```"
    ]
   },
@@ -403,6 +404,29 @@
     "await model_client.close()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Also, as Gemini adds new models, you may need to define the models capabilities via the model_info field. For example, to use `gemini-2.0-flash-lite` or a similar new model, you can use the following code:\n",
+    "\n",
+    "```python \n",
+    "from autogen_core.models import UserMessage\n",
+    "from autogen_ext.models.openai import OpenAIChatCompletionClient\n",
+    "from autogen_core.models import ModelInfo\n",
+    "\n",
+    "model_client = OpenAIChatCompletionClient(\n",
+    "    model=\"gemini-2.0-flash-lite\",\n",
+    "    model_info=ModelInfo(vision=True, function_calling=True, json_output=True, family=\"unknown\", structured_output=True)\n",
+    "    # api_key=\"GEMINI_API_KEY\",\n",
+    ")\n",
+    "\n",
+    "response = await model_client.create([UserMessage(content=\"What is the capital of France?\", source=\"user\")])\n",
+    "print(response)\n",
+    "await model_client.close()\n",
+    "```"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -516,7 +540,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.7"
+   "version": "3.11.9"
   }
  },
  "nbformat": 4,