docs(local model routing): add docs on how to use Gemma for local model routing (#21365)

Co-authored-by: Douglas Reid <21148125+douglas-reid@users.noreply.github.com>
Co-authored-by: Allen Hutchison <adh@google.com>
Co-authored-by: matt korwel <matt.korwel@gmail.com>
This commit is contained in:
Douglas Reid
2026-03-12 14:36:32 -07:00
committed by GitHub
parent ceb4c5f6a7
commit 5abc170b08
3 changed files with 213 additions and 1 deletions

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@@ -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`

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@@ -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

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@@ -0,0 +1,193 @@
# 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`
> **Note**: MacOS can be configured to only allows binaries from "App Store &
> Known Developers". If you encounter an error message when attempting to run
> the binary, you will need to allow the application. One option is to visit
> `System Settings -> Privacy & Security`, scroll to `Security`, and click
> `"Allow Anyway"` for `"lit.macos_arm64"`. Another option is to run
> `xattr -d com.apple.quarantine lit.macos_arm64` from the commandline.
### 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.
#### Windows
```bash
$ .\lit.windows_x86_64.exe 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.
```
#### Linux
```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.
```
#### MacOS
```bash
$ ./lit.lit.macos_arm64 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.**