New models for image generation and text embeddings are now available in Amazon SageMaker JumpStart

Today, AWS announced the availability of FLUX.2-klein-base-4B and Qwen3-Embedding-0.6B in Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers. These models from Black Forest Labs and Qwen bring state-of-the-art image generation and multilingual text embedding capabilities, enabling customers to build creative AI applications and intelligent search systems on AWS infrastructure. These models address different enterprise AI challenges with specialized capabilities:**FLUX.2-klein-base-4B** excels at real-time image generation and multi-reference editing in a compact architecture, delivering state-of-the-art quality that runs on consumer hardware with as little as 13GB VRAM. It is ideal for creative content pipelines, product visualization, rapid prototyping, and applications that require high-quality image synthesis without sacrificing speed.**Qwen3-Embedding-0.6B** excels at text embedding for retrieval, classification, clustering, and bitext mining across 100+ languages, with flexible output dimensions and instruction-aware embeddings. It is ideal for building semantic search systems, RAG pipelines, multilingual document retrieval, and applications that require efficient, high-quality text representations at scale. With SageMaker JumpStart, customers can deploy any of these models with just a few clicks to address their specific AI use cases. To get started with these models, navigate to the Models section of SageMaker Studio or use the SageMaker Python SDK to deploy the models to your AWS account. For more information about deploying and using foundation models in SageMaker JumpStart, see the [](https://docs.aws.amazon.com/sagemaker/latest/dg/studio-jumpstart.html)Amazon SageMaker JumpStart documentation.