diff --git a/conda/environments/all_cuda-125_arch-x86_64.yaml b/conda/environments/all_cuda-128_arch-x86_64.yaml
similarity index 94%
rename from conda/environments/all_cuda-125_arch-x86_64.yaml
rename to conda/environments/all_cuda-128_arch-x86_64.yaml
index 52b0da6f..73eb355d 100644
--- a/conda/environments/all_cuda-125_arch-x86_64.yaml
+++ b/conda/environments/all_cuda-128_arch-x86_64.yaml
@@ -10,7 +10,7 @@ dependencies:
 - click >=8.1
 - cuda-nvcc-impl
 - cuda-nvrtc
-- cuda-version=12.5
+- cuda-version=12.8
 - cudf==25.2.*,>=0.0.0a0
 - dask-cudf==25.2.*,>=0.0.0a0
 - distributed-ucxx==0.42.*,>=0.0.0a0
@@ -34,4 +34,4 @@ dependencies:
 - ucx-py==0.42.*,>=0.0.0a0
 - ucxx==0.42.*,>=0.0.0a0
 - zict>=2.0.0
-name: all_cuda-125_arch-x86_64
+name: all_cuda-128_arch-x86_64
diff --git a/dependencies.yaml b/dependencies.yaml
index 4d1845a5..b5a320f8 100644
--- a/dependencies.yaml
+++ b/dependencies.yaml
@@ -3,7 +3,7 @@ files:
   all:
     output: conda
     matrix:
-      cuda: ["11.4", "11.8", "12.5"]
+      cuda: ["11.4", "11.8", "12.8"]
       arch: [x86_64]
     includes:
       - build_python
@@ -96,6 +96,10 @@ dependencies:
               cuda: "12.5"
             packages:
               - cuda-version=12.5
+          - matrix:
+              cuda: "12.8"
+            packages:
+              - cuda-version=12.8
   cuda:
     specific:
       - output_types: conda
diff --git a/docs/source/install.rst b/docs/source/install.rst
index 43082a67..7c7fa6cb 100644
--- a/docs/source/install.rst
+++ b/docs/source/install.rst
@@ -12,11 +12,11 @@ To use Dask-CUDA on your system, you will need:
 - A version of NVIDIA CUDA Toolkit compatible with the installed driver version; see Table 1 of `CUDA Compatibility -- Binary Compatibility <https://docs.nvidia.com/deploy/cuda-compatibility/index.html#binary-compatibility>`_ for an overview of CUDA Toolkit driver requirements
 
 Once the proper CUDA Toolkit version has been determined, it can be installed using along with Dask-CUDA using ``conda``.
-To install the latest version of Dask-CUDA along with CUDA Toolkit 12.5:
+To install the latest version of Dask-CUDA along with the CUDA Toolkit:
 
 .. code-block:: bash
 
-    conda install -c rapidsai -c conda-forge -c nvidia dask-cuda cuda-version=12.5
+    conda install -c rapidsai -c conda-forge -c nvidia dask-cuda cuda-version=12.8
 
 Pip
 ---