docs: Update GPU table column headers and clarify runpodctl GPU ID requirements (#459)

Co-authored-by: promptless[bot] <179508745+promptless[bot]@users.noreply.github.com>

Author: promptless[bot]

references/gpu-types.mdx

@@ -10,7 +10,7 @@ For information on pricing, see [GPU pricing](https://www.runpod.io/gpu-instance
 This table lists all GPU types available on Runpod:
 {/* Table last generated: 2025-08-23 */}
 
-| GPU Name                                          | GPU ID             |   Memory (GB) |
+| GPU ID                                            | Display Name             |   Memory (GB) |
 |---------------------------------------------------|--------------------------|---------------|
 | AMD Instinct MI300X OAM                           | MI300X                   |           192 |
 | NVIDIA A100 80GB PCIe                             | A100 PCIe                |            80 |

runpodctl/reference/runpodctl-create-pod.mdx

@@ -16,7 +16,7 @@ Create a Pod with 2 RTX 4090 GPUs in the Secure Cloud with a custom container im
 ```sh
 runpodctl create pod \
   --name "my-training-pod" \
-  --gpuType "RTX 4090" \
+  --gpuType "NVIDIA GeForce RTX 3090" \
   --gpuCount 2 \
   --secureCloud \
   --imageName "runpod/pytorch:2.0.1-py3.10-cuda11.8.0-devel" \
@@ -31,7 +31,7 @@ A custom name for your Pod to make it easy to identify and reference.
 </ResponseField>
 
 <ResponseField name="--gpuType" type="string">
-The GPU type to use for the Pod (e.g., `RTX 4090`, `A100 80GB`, `H100 SXM`). Use the GPU ID from the [GPU types reference](/references/gpu-types) table to specify the GPU type.
+The GPU type to use for the Pod (e.g., `NVIDIA GeForce RTX 4090`, `NVIDIA B200`, `NVIDIA L40S`). Use the GPU ID (long form) from the [GPU types reference](/references/gpu-types) table to specify the GPU type.
 </ResponseField>
 
 <ResponseField name="--gpuCount" type="integer" default={1}>

runpodctl/reference/runpodctl-create-pods.mdx

@@ -17,7 +17,7 @@ Create 3 identical Pods with the name "training-worker" in the Secure Cloud:
 runpodctl create pods 
   --name "training-worker" \
   --podCount 3 \
-  --gpuType "A100 80GB" \
+  --gpuType "NVIDIA GeForce RTX 3090" \
   --gpuCount 1 \
   --secureCloud \
   --imageName "runpod/pytorch:2.0.1-py3.10-cuda11.8.0-devel"
@@ -34,7 +34,7 @@ The number of Pods to create.
 </ResponseField>
 
 <ResponseField name="--gpuType" type="string">
-The GPU type to use for the Pod (e.g., `RTX 4090`, `A100 80GB`, `H100 SXM`). Use the GPU ID from the [GPU types reference](/references/gpu-types) table to specify the GPU type.
+The GPU type to use for the Pods (e.g., `NVIDIA GeForce RTX 4090`, `NVIDIA B200`, `NVIDIA L40S`). Use the GPU ID (long form) from the [GPU types reference](/references/gpu-types) table to specify the GPU type.
 </ResponseField>
 
 <ResponseField name="--gpuCount" type="integer" default={1}>