Amazon SageMaker AI now supports serverless model customization for Qwen3.5 models

Amazon SageMaker AI Updates

Amazon SageMaker AI now supports serverless model customization for Qwen3.5, enabling fine-tuning of Qwen3.5 4B, 9B, and 27B parameter models using supervised fine-tuning (SFT) and reinforcement fine-tuning (RFT). This feature allows you to adapt these models to your specific domains and workflows using your proprietary data.

With serverless customization, SageMaker AI manages infrastructure provisioning and training orchestration, so you can focus on your data and evaluation. This service is available in US East (N. Virginia), US West (Oregon), Asia Pacific (Tokyo), and EU (Ireland). To start, navigate to the Models page in Amazon SageMaker Studio or use the SageMaker Python SDK for programmatic access.

What to do

• Launch a customization job via the Models page in Amazon SageMaker Studio.
• Use the SageMaker Python SDK for programmatic access.
• Refer to the Amazon SageMaker AI model customization documentation for more details.

Source: AWS release notes

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