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E-MapReduce:Model service

Last Updated:Sep 15, 2026

EMR Serverless Spark provides built-in models that you can invoke directly with AI Functions or with the Daft operators in the multimodal operator marketplace. You can also register external model services that integrate with Alibaba Cloud Model Studio, PAI-EAS, or self-hosted endpoints.

Prerequisite

To use this feature, activate AI Center first.

Built-in models

The following models are built into EMR Serverless Spark and require no registration. Text generation models and embedding models can be invoked directly with AI Functions or with the Daft operators in the multimodal operator marketplace. The built-in Model Manager serves these models, so you do not need to configure endpoints or credentials.

Model service name

Model name

qwen3.6-plus

qwen3.6-plus

qwen3.5-plus

qwen3.5-plus

qwen-plus

qwen-plus

text-embedding-v4

text-embedding-v4

tongyi-embedding-vision-plus

tongyi-embedding-vision-plus

qwen-audio-3.0-tts-plus

qwen-audio-3.0-tts-plus

qwen-audio-3.0-tts-flash

qwen-audio-3.0-tts-flash

qwen-audio-3.0-asr-flash

qwen-audio-3.0-asr-flash

Built-in models are billed by usage, and the metering unit varies by model type: text generation models and embedding models are metered by token, speech synthesis models by character count, and speech recognition models by audio duration. For the unit price in each region, see Model calls (pay-as-you-go).

Note

The tongyi-embedding-vision-plus model is available only in the Indonesia (Jakarta) and Philippines (Manila) regions. The other built-in models are available in China (Hangzhou), China (Shenzhen), China (Beijing), China (Shanghai), China (Hong Kong), Singapore, Germany (Frankfurt), US (Virginia), US (Silicon Valley), Japan (Tokyo), Indonesia (Jakarta), Philippines (Manila), and Mexico.

Add an external model service

If the built-in models do not meet your needs, follow these steps to register an external model service.

  1. Go to the model service page.

    1. Log in to the E-MapReduce console.

    2. In the left-side navigation pane, select EMR Serverless > Spark.

    3. On the Spark page, click the name of the target workspace.

    4. On the EMR Serverless Spark page, click AI Center > Model Service in the left-side navigation pane.

  2. On the Model Service tab, click Create External Model Service and configure the following parameters:

    Parameter

    Example

    Description

    model service name

    my_qwen_service

    Used as the endpointName input parameter in a subsequent AI Function call. The name must be unique within the workspace and cannot be modified after creation.

    endpoint

    http://12*******39.vpc.cn-hangzhou.pai-eas.aliyuncs.com/api/predict/<ServiceName>/v1

    Enter the endpoint of the external model service. If you use a PAI-EAS model, append /v1 to the end of the endpoint.

    Note

    If the model service provides a public network endpoint, you must configure a network connection with public network access to allow the Spark job to use this model. For more information, see network connection.

    model name

    Qwen3.5-Plus

    The model name to use when you call the service.

    model type

    Chat

    Select Chat or Embedding based on the deployed model type.

    API key

    nMzI**********************Zg==

    The API key for the model service.

    Description

    The latest Qwen multimodal model service

    A brief description for easier identification.

  3. After you confirm the settings are correct, click create to register the model service.

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