From b04f6d0eb3e3791ed17cc8f4e791181607bad397 Mon Sep 17 00:00:00 2001
From: "mintlify[bot]" <109931778+mintlify[bot]@users.noreply.github.com>
Date: Wed, 13 May 2026 17:44:41 +0000
Subject: [PATCH] Document full p5 GPU instance family

Generated-By: mintlify-agent
---
 cloud-accounts/node-groups.mdx |  4 +++-
 other/gpu-workloads.mdx        | 20 +++++++++++++++++++-
 2 files changed, 22 insertions(+), 2 deletions(-)

diff --git a/cloud-accounts/node-groups.mdx b/cloud-accounts/node-groups.mdx
index 50d1df3..64d5e64 100644
--- a/cloud-accounts/node-groups.mdx
+++ b/cloud-accounts/node-groups.mdx
@@ -112,9 +112,11 @@ Create custom node groups for specialized workloads like GPU processing, high-me
 
         <Info>
         For GPU workloads, select instances with GPU support:
-        - **AWS**: `g4dn.xlarge`, `p3.2xlarge`
+        - **AWS**: `g4dn.xlarge`, `p3.2xlarge`, `p4d.24xlarge`, `p5.4xlarge`, `p5.48xlarge`, `p5e.48xlarge`, `p5en.48xlarge`
         - **Azure**: `Standard_NC4as_T4_v3`
         - **GCP**: `g2-standard-4`
+
+        See [Running GPU workloads](/other/gpu-workloads#supported-gpu-instance-types) for the full list of supported GPU instance types and their specs.
         </Info>
       </Tab>
     </Tabs>
diff --git a/other/gpu-workloads.mdx b/other/gpu-workloads.mdx
index 601b865..19006a0 100644
--- a/other/gpu-workloads.mdx
+++ b/other/gpu-workloads.mdx
@@ -35,7 +35,7 @@ CPU workloads.
 
     | Setting | Description |
     |---------|-------------|
-    | **Instance type** | Select a GPU-enabled instance type (see table below) |
+    | **Instance type** | Select a GPU-enabled instance type (see [Supported GPU instance types](#supported-gpu-instance-types) below) |
     | **Minimum nodes** | Select minimum number of nodes that will be available at all times |
     | **Maximum nodes** | The upper limit for autoscaling based on demand |
 
@@ -51,6 +51,24 @@ CPU workloads.
   </Step>
 </Steps>
 
+## Supported GPU instance types
+
+Porter supports a range of NVIDIA GPU instance types on AWS. Choose the instance that matches your workload's compute, memory, and VRAM requirements.
+
+| Instance type | vCPUs | RAM | GPUs | GPU type | GPU memory |
+|---------------|-------|-----|------|----------|------------|
+| `g4dn.xlarge` | 4 | 16 GiB | 1 | NVIDIA T4 | 16 GB |
+| `p3.2xlarge` | 8 | 61 GiB | 1 | NVIDIA V100 | 16 GB |
+| `p4d.24xlarge` | 96 | 1,152 GiB | 8 | NVIDIA A100 | 320 GB |
+| `p5.4xlarge` | 16 | 256 GiB | 1 | NVIDIA H100 | 80 GB |
+| `p5.48xlarge` | 192 | 2 TiB | 8 | NVIDIA H100 | 640 GB |
+| `p5e.48xlarge` | 192 | 2 TiB | 8 | NVIDIA H200 | 1,128 GB |
+| `p5en.48xlarge` | 192 | 2 TiB | 8 | NVIDIA H200 | 1,128 GB |
+
+<Info>
+  The full p5 family (`p5.4xlarge`, `p5.48xlarge`, `p5e.48xlarge`, and `p5en.48xlarge`) is suited for large-scale training and inference of foundation models. Use `p5.4xlarge` for single-GPU H100 workloads, and the `p5e`/`p5en` variants when you need H200 GPUs with expanded VRAM for larger models. Availability varies by region — check the AWS console for the latest region support.
+</Info>
+
 ## Deploying a GPU Application
 
 Once your GPU node group is ready, you can deploy applications that use GPU resources.