diff --git a/_vale/config/vocabularies/Docker/accept.txt b/_vale/config/vocabularies/Docker/accept.txt
index 0370dcd7c1..fb8c78ea76 100644
--- a/_vale/config/vocabularies/Docker/accept.txt
+++ b/_vale/config/vocabularies/Docker/accept.txt
@@ -170,6 +170,7 @@ Quickview
 rebalance
 reimplement
 Rekor
+ROCm
 rollback
 rootful
 runc
@@ -213,6 +214,7 @@ Visual Studio Code
 VMware
 vpnkit
 vSphere
+Vulkan
 Vue
 Wasm
 Wasmtime
diff --git a/content/manuals/ai/model-runner/_index.md b/content/manuals/ai/model-runner/_index.md
index d0a61b153e..8c6b2e51e7 100644
--- a/content/manuals/ai/model-runner/_index.md
+++ b/content/manuals/ai/model-runner/_index.md
@@ -6,7 +6,7 @@ params:
     group: AI
 weight: 30
 description: Learn how to use Docker Model Runner to manage and run AI models.
-keywords: Docker, ai, model runner, docker desktop, docker engine, llm
+keywords: Docker, ai, model runner, docker desktop, docker engine, llm, openai, llama.cpp, vllm, cpu, nvidia, cuda, amd, rocm, vulkan
 aliases:
   - /desktop/features/model-runner/
   - /model-runner/
@@ -34,7 +34,8 @@ with AI models locally.
 
 - [Pull and push models to and from Docker Hub](https://hub.docker.com/u/ai)
 - Serve models on OpenAI-compatible APIs for easy integration with existing apps
-- Package GGUF files as OCI Artifacts and publish them to any Container Registry
+- Support for both llama.cpp and vLLM inference engines (vLLM currently supported on Linux x86_64/amd64 with NVIDIA GPUs only)
+- Package GGUF and Safetensors files as OCI Artifacts and publish them to any Container Registry
 - Run and interact with AI models directly from the command line or from the Docker Desktop GUI
 - Manage local models and display logs
 - Display prompt and response details
@@ -68,8 +69,8 @@ Windows(arm64):
 
 Docker Engine only:
 
-- Linux CPU & Linux NVIDIA
-- NVIDIA drivers 575.57.08+
+- Supports CPU, NVIDIA (CUDA), AMD (ROCm), and Vulkan backends
+- Requires NVIDIA driver 575.57.08+ when using NVIDIA GPUs
 
 {{< /tab >}}
 {{</tabs >}}
@@ -83,6 +84,8 @@ initial pull may take some time. After that, they're cached locally for faster
 access. You can interact with the model using
 [OpenAI-compatible APIs](api-reference.md).
 
+Docker Model Runner supports both [llama.cpp](https://github.com/ggerganov/llama.cpp) and [vLLM](https://github.com/vllm-project/vllm) as inference engines, providing flexibility for different model formats and performance requirements. For more details, see the [Docker Model Runner repository](https://github.com/docker/model-runner).
+
 > [!TIP]
 >
 > Using Testcontainers or Docker Compose?
@@ -111,14 +114,9 @@ $ ln -s /Applications/Docker.app/Contents/Resources/cli-plugins/docker-model ~/.
 
 Once linked, rerun the command.
 
-### No consistent digest support in Model CLI
-
-The Docker Model CLI currently lacks consistent support for specifying models by image digest. As a temporary workaround, you should refer to models by name instead of digest.
-
 ## Share feedback
 
-Thanks for trying out Docker Model Runner. Give feedback or report any bugs
-you may find through the **Give feedback** link next to the **Enable Docker Model Runner** setting.
+Thanks for trying out Docker Model Runner. To report bugs or request features, [open an issue on GitHub](https://github.com/docker/model-runner/issues). You can also give feedback through the **Give feedback** link next to the **Enable Docker Model Runner** setting.
 
 ## Next steps