Blog Go to console

    Configuration options for hybrid experiences in Android apps


    This page describes the following configuration options for hybrid experiences:

    Make sure that you've completed the getting started guide for building hybrid experiences .

    Set an inference mode

    The examples in the getting started guide use the PREFER_ON_DEVICE mode, but this is only one of the four available inference modes .

    Here are the available inference modes:

    • PREFER_ON_DEVICE : Attempt to use the on-device model if it's available and supports the type of request. Otherwise, log an error on the device and then automatically fall back to the cloud-hosted model .

      Kotlin 

        val 
  
 config 
  
 = 
  
 OnDeviceConfig 
 ( 
 mode 
  
 = 
  
 InferenceMode 
 . 
 PREFER_ON_DEVICE 
 )

      Java 

        InferenceMode 
  
 mode 
  
 = 
  
 InferenceMode 
 . 
 PREFER_ON_DEVICE 
 ; 
 OnDeviceConfig 
  
 config 
  
 = 
  
 new 
  
 OnDeviceConfig 
 ( 
 mode 
 );

    • ONLY_ON_DEVICE : Attempt to use the on-device model if it's available and supports the type of request. Otherwise, throw an exception .

      Kotlin 

        val 
  
 config 
  
 = 
  
 OnDeviceConfig 
 ( 
 mode 
  
 = 
  
 InferenceMode 
 . 
 ONLY_ON_DEVICE 
 )

      Java 

        InferenceMode 
  
 mode 
  
 = 
  
 InferenceMode 
 . 
 ONLY_ON_DEVICE 
 ; 
 OnDeviceConfig 
  
 config 
  
 = 
  
 new 
  
 OnDeviceConfig 
 ( 
 mode 
 );

    • PREFER_IN_CLOUD : Attempt to use the cloud-hosted model if the device is online and if the model is available. If the device is offline, fall back to the on-device model . In all other failure cases, throw an exception .

      Kotlin 

        val 
  
 config 
  
 = 
  
 OnDeviceConfig 
 ( 
 mode 
  
 = 
  
 InferenceMode 
 . 
 PREFER_IN_CLOUD 
 )

      Java 

        InferenceMode 
  
 mode 
  
 = 
  
 InferenceMode 
 . 
 PREFER_IN_CLOUD 
 ; 
 OnDeviceConfig 
  
 config 
  
 = 
  
 new 
  
 OnDeviceConfig 
 ( 
 mode 
 );

    • ONLY_IN_CLOUD : Attempt to use the cloud-hosted model if the device is online and if the model is available. Otherwise, throw an exception .

      Kotlin 

        val 
  
 config 
  
 = 
  
 OnDeviceConfig 
 ( 
 mode 
  
 = 
  
 InferenceMode 
 . 
 ONLY_IN_CLOUD 
 )

      Java 

        InferenceMode 
  
 mode 
  
 = 
  
 InferenceMode 
 . 
 ONLY_IN_CLOUD 
 ; 
 OnDeviceConfig 
  
 config 
  
 = 
  
 new 
  
 OnDeviceConfig 
 ( 
 mode 
 );

    Determine whether on-device or in-cloud inference was used

    If your inference mode is PREFER_ON_DEVICE or PREFER_IN_CLOUD , then it might be helpful to know which mode was used for given requests. This information is provided by the inferenceSource property of each response.

    When you access this property, the returned value will be either ON_DEVICE or IN_CLOUD .

    Kotlin 

      // ... 
 print 
 ( 
 "You used: 
 ${ 
 result 
 . 
 response 
 . 
 inferenceSource 
 } 
 " 
 ) 
 print 
 ( 
 result 
 . 
 response 
 . 
 text 
 )

    Java 

      // ... 
 System 
 . 
 out 
 . 
 println 
 ( 
 "You used: " 
  
 + 
  
 result 
 . 
 getResponse 
 (). 
 getInferenceSource 
 ()); 
 System 
 . 
 out 
 . 
 println 
 ( 
 result 
 . 
 getResponse 
 (). 
 getText 
 ());

    Specify a model to use

    Click your Gemini API provider to view provider-specific content and code on this page.

    You can specify a model to use when you create the generativeModel instance ( Kotlin | Java ).

    • Specify a cloud-hosted model:

      • If your inference mode is PREFER_ON_DEVICE , PREFER_IN_CLOUD , or ONLY_IN_CLOUD , then you must explicitly specify a cloud-hosted model to use. The SDK does not have a default cloud-hosted model.

      • Find model names for all supported cloud-hosted Gemini models .

    • Specify an on-device model:

      • If your inference mode is PREFER_ON_DEVICE , PREFER_IN_CLOUD , or ONLY_ON_DEVICE , then you can optionally specify in the onDeviceConfig a "category" of on-device model to use. Categories are a combination of release stage and performance characteristics.

      • Supported category values are listed below.
        AICore auto-selects the on-device model that meets the conditions of the specified category and is supported by the device. For example, if you specify PREVIEW and the device is a Pixel 9, then Gemini Nano 4 Full [Preview] ( nano-v4-full ) would likely be auto-selected.

        • STABLE : The latest stable on-device model.

          • Fully tested and on consumer devices.

          • For example, Gemini Nano 3 ( nano-v3 ) or Gemini Nano 2 ( nano-v2 ).

          • Default setting for the on-device model if no OnDeviceModelOption is specified.

        • PREVIEW : The latest preview on-device model with full performance capabilities.

          • Designed for higher reasoning power and complex tasks.

          • For example, Gemini Nano 4 Full [Preview] ( nano-v4-full , which is based on Gemma 4 E4B).

        • PREVIEW_FAST : The latest preview on-device model that's fast .

          • Optimized for maximum speed and lower latency.

          • For example, Gemini Nano 4 Fast [Preview] ( nano-v4-fast , which is based on Gemma 4 E2B).

    Kotlin 

      val 
  
 model 
  
 = 
  
 Firebase 
 . 
 ai 
 ( 
 backend 
  
 = 
  
 GenerativeBackend 
 . 
 googleAI 
 ()) 
  
 . 
 generativeModel 
 ( 
  
 // Specify a cloud-hosted model. 
  
 // Required for `PREFER_ON_DEVICE`, `PREFER_IN_CLOUD`, and `ONLY_IN_CLOUD` inference modes. 
  
 modelName 
  
 = 
  
 " CLOUD_HOSTED_MODEL_NAME 
" 
 , 
  
 onDeviceConfig 
  
 = 
  
 OnDeviceConfig 
 ( 
  
 mode 
  
 = 
  
 InferenceMode 
 . 
  INFERENCE_MODE 
 
 , 
  
 // (Optional) Specify an on-device model category. 
  
 // AICore will auto-select an on-device model based on this category. 
  
 // If not specified, AICore will auto-select the default stable on-device model. 
  
 modelOption 
  
 = 
  
 OnDeviceModelOption 
 . 
  ON 
 - 
 DEVICE_MODEL_CATEGORY 
 
 ) 
  
 )

    Java 

      GenerativeModel 
  
 ai 
  
 = 
  
 FirebaseAI 
 . 
 getInstance 
 ( 
 GenerativeBackend 
 . 
 googleAI 
 ()) 
  
 . 
 generativeModel 
 ( 
  
 // Specify a cloud-hosted model. 
  
 // Required for `PREFER_ON_DEVICE`, `PREFER_IN_CLOUD`, and `ONLY_IN_CLOUD` inference modes. 
  
 " CLOUD_HOSTED_MODEL_NAME 
" 
 , 
  
 /* config = */ 
  
 null 
 , 
  
 /* safetySettings = */ 
  
 null 
 , 
  
 /* tools = */ 
  
 null 
 , 
  
 /* toolConfig = */ 
  
 null 
 , 
  
 /* systemInstruction = */ 
  
 null 
 , 
  
 /* requestOptions = */ 
  
 new 
  
 RequestOptions 
 (), 
  
 new 
  
 OnDeviceConfig 
 ( 
  
 /* mode = */ 
  
 InferenceMode 
 . 
  INFERENCE_MODE 
 
 , 
  
 /* maxOutputTokens = */ 
  
 null 
 , 
  
 /* temperature = */ 
  
 null 
 , 
  
 /* topK = */ 
  
 null 
 , 
  
 /* seed = */ 
  
 null 
 , 
  
 /* candidateCount = */ 
  
 1 
 , 
  
 // (Optional) Specify an on-device model category. 
  
 // AICore will auto-select an on-device model based on this category. 
  
 // If not specified, AICore will auto-select the default stable on-device model. 
  
 /* modelOption = */ 
  
 OnDeviceModelOption 
 . 
  ON 
 - 
 DEVICE_MODEL_CATEGORY 
 
 ) 
  
 ); 
 GenerativeModelFutures 
  
 model 
  
 = 
  
 GenerativeModelFutures 
 . 
 from 
 ( 
 ai 
 );

    Use model configuration to control responses

    Click your Gemini API provider to view provider-specific content and code on this page.

    In each request to a model, you can send along a model configuration to control how the model generates a response. Cloud-hosted models and on-device models offer different configuration options ( cloud vs on-device parameters).

    For cloud-hosted models, set their configuration directly in the model's configuration. However, for the on-device models, set their configuration within an onDeviceConfig .

    The configuration is maintained for the lifetime of the instance. If you want to use a different config, create a new GenerativeModel instance with that config.

    Here's an example that sets the configurations for the cloud-hosted and on-device models that could be used if PREFER_ON_DEVICE inference mode is set:

    Kotlin 

      val 
  
 model 
  
 = 
  
 Firebase 
 . 
 ai 
 ( 
 backend 
  
 = 
  
 GenerativeBackend 
 . 
 googleAI 
 ()) 
  
 . 
 generativeModel 
 ( 
 " MODEL_NAME 
" 
 , 
  
 // Config for cloud-hosted model 
  
 generationConfig 
  
 = 
  
 generationConfig 
  
 { 
  
 temperature 
  
 = 
  
 0.8f 
 , 
  
 topK 
  
 = 
  
 10 
  
 }, 
  
 // Config for on-device model 
  
 onDeviceConfig 
  
 = 
  
 onDeviceConfig 
  
 { 
  
 mode 
  
 = 
  
 InferenceMode 
 . 
 PREFER_ON_DEVICE 
 , 
  
 temperature 
  
 = 
  
 0.8f 
 , 
  
 topK 
  
 = 
  
 5 
  
 })

    Java 

      // Config for cloud-hosted model 
 GenerationConfig 
  
 generationConfig 
  
 = 
  
 new 
  
 GenerationConfig 
 . 
 Builder 
 () 
  
 . 
 setTemperature 
 ( 
 0.8f 
 ) 
  
 . 
 setTopK 
 ( 
 10 
 ) 
  
 . 
 build 
 (); 
 // Config for on-device model 
 OnDeviceConfig 
  
 onDeviceConfig 
  
 = 
  
 new 
  
 OnDeviceConfig 
 . 
 Builder 
 () 
  
 . 
 setMode 
 ( 
 InferenceMode 
 . 
 PREFER_ON_DEVICE 
 ) 
  
 . 
 setTemperature 
 ( 
 0.8f 
 ) 
  
 . 
 setTopK 
 ( 
 5 
 ) 
  
 . 
 build 
 (); 
 GenerativeModel 
  
 ai 
  
 = 
  
 FirebaseAI 
 . 
 getInstance 
 ( 
 GenerativeBackend 
 . 
 googleAI 
 ()) 
  
 . 
 generativeModel 
 ( 
  
 " MODEL_NAME 
" 
 , 
  
 generationConfig 
 , 
  
 onDeviceConfig 
  
 ); 
 GenerativeModelFutures 
  
 model 
  
 = 
  
 GenerativeModelFutures 
 . 
 from 
 ( 
 ai 
 );
    Create a Mobile Website
    View Site in Mobile | Classic
    Share by: