diff --git a/openfl-tutorials/experimental/Workflow_Interface_201_Exclusive_GPUs_with_Ray.ipynb b/openfl-tutorials/experimental/Workflow_Interface_201_Exclusive_GPUs_with_Ray.ipynb
index 05cb58bb920..f37443f11e8 100644
--- a/openfl-tutorials/experimental/Workflow_Interface_201_Exclusive_GPUs_with_Ray.ipynb
+++ b/openfl-tutorials/experimental/Workflow_Interface_201_Exclusive_GPUs_with_Ray.ipynb
@@ -291,7 +291,7 @@
    "source": [
     "In this step we define entities necessary to run the flow and create a function which returns dataset as private attributes of collaborator. As described in [quickstart](https://github.com/securefederatedai/openfl/blob/develop/openfl-tutorials/experimental/Workflow_Interface_101_MNIST.ipynb) we define entities necessary for the flow.\n",
     "\n",
-    "To request GPU(s) with ray-backend, we specify `num_gpus=0.5` as the argument while instantiating Collaborator, this will reserve 0.5 GPU for each of the 2 collaborators and therefore require a dedicated GPU for the exeriment. Tune this based on your use case, for example `num_gpus=0.5` for an experiment with 4 collaborators will require 2 dedicated GPUs. **NOTE:** Collaborator cannot span over multiple GPUs, for example `num_gpus=0.4` with 5 collaborators will require 3 dedicated GPUs. In this case collaborator 1 and 2 use GPU#1, collaborator 3 and 4 use GPU#2, and collaborator 5 uses GPU#3."
+    "To request GPU(s) with ray-backend, we specify `num_gpus=0.3` as the argument while instantiating Aggregator and Collaborator, this will reserve 0.3 GPU for each of the 2 collaborators and the aggregator and therefore require a dedicated GPU for the experiment. Tune this based on your use case, for example `num_gpus=0.4` for an experiment with 4 collaborators and the aggregator will require 2 dedicated GPUs. **NOTE:** Collaborator cannot span over multiple GPUs, for example `num_gpus=0.4` with 5 collaborators will require 3 dedicated GPUs. In this case collaborator 1 and 2 use GPU#1, collaborator 3 and 4 use GPU#2, and collaborator 5 uses GPU#3."
    ]
   },
   {
@@ -302,7 +302,7 @@
    "outputs": [],
    "source": [
     "# Setup Aggregator private attributes via callable function\n",
-    "aggregator = Aggregator()\n",
+    "aggregator = Aggregator(num_gpus=0.3)\n",
     "\n",
     "collaborator_names = ['Portland', 'Seattle']\n",
     "\n",
@@ -325,7 +325,7 @@
     "for idx, collaborator_name in enumerate(collaborator_names):\n",
     "    collaborators.append(\n",
     "        Collaborator(\n",
-    "            name=collaborator_name, num_cpus=0, num_gpus=0.5,\n",
+    "            name=collaborator_name, num_cpus=0, num_gpus=0.3,\n",
     "            private_attributes_callable=callable_to_initialize_collaborator_private_attributes,\n",
     "            index=idx, n_collaborators=len(collaborator_names),\n",
     "            train_dataset=mnist_train, test_dataset=mnist_test, batch_size_train=batch_size_train\n",