docs(local model routing): add docs on how to use Gemma for local model routing

docs/cli/model-routing.md

@@ -26,6 +26,20 @@ policies.
     the CLI will use an available fallback model for the current turn or the
     remainder of the session.
 
+### Local Model Routing (Experimental)
+
+Gemini CLI supports using a local model for routing decisions. When configured,
+Gemini CLI will use a locally-running **Gemma** model to make routing decisions
+(instead of sending routing decisions to a hosted model). This feature can help
+reduce costs associated with hosted model usage while offering similar routing
+decision latency and quality.
+
+In order to use this feature, the local Gemma model **must** be served behind a
+Gemini API and accessible via HTTP at an endpoint configured in `settings.json`.
+
+For more details on how to configure local model routing, see
+[Local Model Routing](../core/local-model-routing.md).
+
 ### Model selection precedence
 
 The model used by Gemini CLI is determined by the following order of precedence:
@@ -38,5 +52,8 @@ The model used by Gemini CLI is determined by the following order of precedence:
 3.  **`model.name` in `settings.json`:** If neither of the above are set, the
     model specified in the `model.name` property of your `settings.json` file
     will be used.
-4.  **Default model:** If none of the above are set, the default model will be
+4.  **Local model (experimental):** If the Gemma local model router is enabled
+    in your `settings.json` file, the CLI will use the local Gemma model
+    (instead of Gemini models) to route the request to an appropriate model.
+5.  **Default model:** If none of the above are set, the default model will be
     used. The default model is `auto`

docs/core/index.md

@@ -15,6 +15,8 @@ requests sent from `packages/cli`. For a general overview of Gemini CLI, see the
   modular GEMINI.md import feature using @file.md syntax.
 - **[Policy Engine](../reference/policy-engine.md):** Use the Policy Engine for
   fine-grained control over tool execution.
+- **[Local Model Routing (experimental)](./local-model-routing.md):** Learn how to
+  enable use of a local Gemma model for model routing decisions.
 
 ## Role of the core
 

docs/core/local-model-routing.md

@@ -0,0 +1,144 @@
+# Local Model Routing (experimental)
+
+Gemini CLI supports using a local model for
+[routing decisions](../cli/model-routing.md). When configured, Gemini CLI will
+use a locally-running **Gemma** model to make routing decisions (instead of
+sending routing decisions to a hosted model).
+
+This feature can help reduce costs associated with hosted model usage while
+offering similar routing decision latency and quality.
+
+> **Note: Local model routing is currently an experimental feature.**
+
+## Setup
+
+Using a Gemma model for routing decisions requires that an implementation of a
+Gemma model be running locally on your machine, served behind an HTTP endpoint
+and accessed via the Gemini API.
+
+To serve the Gemma model, follow these steps:
+
+### Download the LiteRT-LM runtime
+
+The [LiteRT-LM](https://github.com/google-ai-edge/LiteRT-LM) runtime offers
+pre-built binaries for locally-serving models. Download the binary appropriate
+for your system.
+
+#### Windows
+
+1. Download
+   [lit.windows_x86_64.exe](https://github.com/google-ai-edge/LiteRT-LM/releases/download/v0.9.0-alpha03/lit.windows_x86_64.exe).
+2. Using GPU on Windows requires the DirectXShaderCompiler. Download the
+   [dxc zip from the latest release](https://github.com/microsoft/DirectXShaderCompiler/releases/download/v1.8.2505.1/dxc_2025_07_14.zip).
+   Unzip the archive and from the architecture-appropriate `bin\` directory, and
+   copy the `dxil.dll` and `dxcompiler.dll` into the same location as you saved
+   `lit.windows_x86_64.exe`.
+3. (Optional) Test starting the runtime:
+   `.\lit.windows_x86_64.exe serve --verbose`
+
+#### Linux
+
+1. Download
+   [lit.linux_x86_64](https://github.com/google-ai-edge/LiteRT-LM/releases/download/v0.9.0-alpha03/lit.linux_x86_64).
+2. Ensure the binary is executable: `chmod a+x lit.linux_x86_64`
+3. (Optional) Test starting the runtime: `./lit.linux_x86_64 serve --verbose`
+
+#### MacOS
+
+1. Download
+   [lit-macos-arm64](https://github.com/google-ai-edge/LiteRT-LM/releases/download/v0.9.0-alpha03/lit.macos_arm64).
+2. Ensure the binary is executable: `chmod a+x lit.macos_arm64`
+3. (Optional) Test starting the runtime: `./lit.macos_arm64 serve --verbose`
+
+### Download the Gemma Model
+
+Before using Gemma, you will need to download the model (and agree to the Terms
+of Service). This can be done via the LiteRT-LM runtime via:
+
+```bash
+$ ./lit.linux_x86_64 pull gemma3-1b-gpu-custom
+
+[Legal] The model you are about to download is governed by
+the Gemma Terms of Use and Prohibited Use Policy. Please review these terms and ensure you agree before continuing.
+
+Full Terms: https://ai.google.dev/gemma/terms
+Prohibited Use Policy: https://ai.google.dev/gemma/prohibited_use_policy
+
+Do you accept these terms? (Y/N): Y
+
+Terms accepted.
+Downloading model 'gemma3-1b-gpu-custom' ...
+Downloading... 968.6 MB
+Download complete.
+```
+
+### Start LiteRT-LM Runtime
+
+Using the command appropriate to your system, start the LiteRT-LM runtime.
+Configure the port that you want to use for your Gemma model. For the purposes
+of this document, we will use port `9379`.
+
+Example command for MacOS: `./lit.macos_arm64 serve --port=9379 --verbose`
+
+### (Optional) Verify Model Serving
+
+Send a quick prompt to the model via HTTP to validate successful model serving.
+This will cause the runtime to download the model and run it once.
+
+You should see a short joke in the server output as an indicator of success.
+
+#### Windows
+
+```
+# Run this in PowerShell to send a request to the server
+
+$uri = "http://localhost:9379/v1beta/models/gemma3-1b-gpu-custom:generateContent"
+$body = @{contents = @( @{
+  role = "user"
+  parts = @( @{ text = "Tell me a joke." } )
+})} | ConvertTo-Json -Depth 10
+
+Invoke-RestMethod -Uri $uri -Method Post -Body $body -ContentType "application/json"
+```
+
+#### Linux/MacOS
+
+```bash
+$ curl "http://localhost:9379/v1beta/models/gemma3-1b-gpu-custom:generateContent" \
+  -H 'Content-Type: application/json' \
+  -X POST \
+  -d '{"contents":[{"role":"user","parts":[{"text":"Tell me a joke."}]}]}'
+```
+
+## Configuration
+
+To use a local Gemma model for routing, you must explicitly enable it in your
+`settings.json`:
+
+```json
+{
+  "experimental": {
+    "gemmaModelRouter": {
+      "enabled": true,
+      "classifier": {
+        "host": "http://localhost:9379",
+        "model": "gemma3-1b-gpu-custom"
+      }
+    }
+  }
+}
+```
+
+> Use the port you started your LiteRT-LM runtime on in the setup steps.
+
+### Configuration schema
+
+| Field              | Type    | Required | Description                                                                                |
+| :----------------- | :------ | :------- | :----------------------------------------------------------------------------------------- |
+| `enabled`          | boolean | Yes      | Must be `true` to enable the feature.                                                      |
+| `classifier`       | object  | Yes      | The configuration for the local model endpoint. It includes the host and model specifiers. |
+| `classifier.host`  | string  | Yes      | The URL to the local model server. Should be `http://localhost:<port>`.                    |
+| `classifier.model` | string  | Yes      | The model name to use for decisions. Must be `"gemma3-1b-gpu-custom"`.                     |
+
+> **Note: You will need to restart after configuration changes for local model
+> routing to take effect.**