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E-MapReduce:Model service

Last Updated:May 14, 2026

EMR Serverless Spark includes built-in models that you can invoke directly using AI Functions. If the built-in models do not meet your needs, register external model services. This feature supports integration with Alibaba Cloud Model Studio, PAI-EAS, and self-hosted model services.

Prerequisite

To use this feature, activate AI Center first.

Built-in models

The following models are built into EMR Serverless Spark and can be invoked directly using AI Functions without registration.

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

Note

The tongyi-embedding-vision-plus AI Function is available only in the following region: Indonesia (Jakarta).

Add an external model service

If the built-in models do not meet your needs, follow these steps to add a self-hosted 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

    The name is used as the value for the endpointName input parameter in a subsequent AI Function, is unique within the workspace, and cannot be modified later.

    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

    Enter a brief description of the service for easier identification.

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

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