superfly · kcmartin · Feb 11, 2026 · Feb 9, 2026 · Feb 10, 2026
diff --git a/about/pricing.html.markerb b/about/pricing.html.markerb
@@ -102,26 +102,6 @@ For example, if you purchase a $36/year `shared` Machines block in `cdg`, you'll
 
 You can set up reservations via self-service in the billing section of your Fly.io [dashboard](https://fly.io/dashboard). They apply to usage starting on the 1st, so setting up reservations any time in the month will give you the credits the entire month.
 
-### GPU-enabled Fly Machines
-
-Pricing for a GPU-enabled Fly Machine is the price of a standard Fly Machine (see above) plus the price of the attached GPU. Like Machines, GPUs are billed by the second when the attached Machine is running.
-
-On-demand GPU pricing:
-
-* A10: $1.50/hr per GPU
-* L40S: $1.25/hr per GPU
-* A100 40G PCIe: $2.50/hr per GPU
-* A100 80G SXM: $3.50/hr per GPU
-
-Usage terms:
-
-* No minimum usage requirements.
-* Customizable CPU, RAM, and storage options.
-
-Reserved and dedicated options:
-
-* Discounted rates for reserved GPU Machines and dedicated hosts.
-
 ## Managed Postgres
 
 The price of running Fly.io Managed Postgres depends on your selected Managed Postgres Plan and the amount of storage your Postgres cluster has. 
@@ -257,6 +237,30 @@ You **will** be billed separately for data transfer to these external third-part
 
 The [Machine price](#compute) and [volume price](#persistent-storage-volumes) for Fly Postgres are the same as any other Machine and volume you'd run on Fly.io. Assuming the Machines are running all the time, the cost for the preset configurations is about $2/month for a single node cluster for dev projects and from about $82 to $164/month for a three-node production cluster. You don't need to keep the preset configurations, you can [scale your Fly Postgres Machines](/docs/postgres/managing/scaling/) to suit your workload at any time.
 
+### GPU-enabled Fly Machines (Deprecated)
+
+<div class="warning icon">
+**GPUs are deprecated and will be unavailable after August 1.**
+</div>
+
+Pricing for a GPU-enabled Fly Machine is the price of a standard Fly Machine (see above) plus the price of the attached GPU. Like Machines, GPUs are billed by the second when the attached Machine is running.
+
+On-demand GPU pricing:
+
+* A10: $0.75/hr per GPU
+* L40S: $0.70/hr per GPU
+* A100 40G PCIe: $1.25/hr per GPU
+* A100 80G SXM: $1.50/hr per GPU
+
+Usage terms:
+
+* No minimum usage requirements.
+* Customizable CPU, RAM, and storage options.
+
+Reserved and dedicated options:
+
+* Discounted rates for reserved GPU Machines and dedicated hosts.
+
 ## Discontinued Plans
 
 Fly.io no longer offers plans to new customers. If you purchased a Launch or Scale plan before October 7, 2024, you can remain on those plans unless you convert to Pay As You Go, delete your payment method, or otherwise stop using Fly.io.

diff --git a/gpus/getting-started-gpus.html.md b/gpus/getting-started-gpus.html.md
@@ -4,6 +4,10 @@ layout: docs
 nav: firecracker
 ---
 
+<div class="warning icon">
+**GPUs are deprecated and will be unavailable after August 1.**
+</div>
+
 ## How do I run a GPU Machine on Fly.io?
 
 A Fly GPU Machine works very similarly to a CPU-only (or "normal") Fly Machine, and has access to the same platform features by default. It boots up with GPU drivers installed and you can run `nvidia-smi` right away. So running a Fly App that uses CUDA compute is a slight variation on running any Fly App. In a nutshell:

diff --git a/gpus/gpu-quickstart.html.markerb b/gpus/gpu-quickstart.html.markerb
@@ -5,6 +5,10 @@ toc: false
 nav: firecracker
 ---
 
+<div class="warning icon">
+**GPUs are deprecated and will be unavailable after August 1.**
+</div>
+
 1. You can use any base image for your Dockerfile, but it is convenient to base it on `ubuntu:22.04` and install libraries from NVIDIA's official apt repository: `RUN apt install -y cuda-nvcc-12-2 libcublas-12-2 libcudnn8` is usually enough.
 
     <div class = "note icon">

diff --git a/gpus/index.html.md b/gpus/index.html.md
@@ -5,6 +5,10 @@ nav: firecracker
 toc: false
 ---
 
+<div class="warning icon">
+**GPUs are deprecated and will be unavailable after August 1.**
+</div>
+
 Fly.io has GPUs! If you have workloads that would benefit from GPU acceleration, Fly GPU Machines may be for you.
 
 <figure class="flex justify-center">

diff --git a/gpus/python-gpu-example.html.md b/gpus/python-gpu-example.html.md
@@ -4,6 +4,10 @@ layout: docs
 nav: firecracker
 ---
 
+<div class="warning icon">
+**GPUs are deprecated and will be unavailable after August 1.**
+</div>
+
 This is a worked example for a CUDA-enabled Python template environment on a Fly GPU Machine, for working with ML models.
 
 We'll start with a minimal Ubuntu Linux, add a non-root user, and set up a Python virtual environment for a project, with Jupyter Notebook installed. NVIDIA libraries that the project uses can be installed to the persistent disk as needed, using pip.

diff --git a/kubernetes/using-gpus.html.markerb b/kubernetes/using-gpus.html.markerb
@@ -5,6 +5,10 @@ toc: false
 nav: firecracker
 ---
 
+<div class="warning icon">
+**GPUs are deprecated and will be unavailable after August 1.**
+</div>
+
 <div class= "important icon">
 Fly Kubernetes is in closed beta and not recommended for critical production usage. To report issues or provide feedback, email us at beta@fly.io.
 </div>