aws AWS What's New ·

Meta's Muse-Glimmer-30B and Alibaba's Qwen 3.8-27B Models Now on SageMaker JumpStart

aiawsgaengineeraws-sagemaker
feature

Amazon SageMaker JumpStart now offers Meta's Muse-Glimmer-30B and Alibaba's Qwen 3.8-27B foundation models, expanding the portfolio of available large language models for AWS customers. These additions provide specialized capabilities for autonomous agentic workflows, multi-step reasoning, coding, and multimodal understanding. The models enable developers and architects to deploy high-performance, scalable AI solutions for various enterprise challenges, from complex tool use to advanced coding and failure recovery. Muse-Glimmer-30B is an Apache 2.0-licensed dense model with 30 billion parameters, ideal for local agentic tasks and sequential tool calls. Qwen 3.8-27B is a 27 billion-parameter native vision-language model, excelling in coding and multimodal agentic tasks with a large context window.

  • Meta Muse-Glimmer-30B for Autonomous Agentic Workflows
  • Alibaba Qwen 3.8-27B for Coding & Multimodal Agentic Tasks
  • Simplified Deployment via SageMaker JumpStart
Features (2)
  • Meta Muse-Glimmer-30B for Autonomous Agentic Workflows

    This 30B-parameter dense model from Meta Superintelligence Lab is engineered for autonomous agentic tasks, offering multi-step reasoning, tool use, and failure recovery. It combines a ~1.8B ViT-G/14 perception encoder with interleaved text/image inputs, a 131K+ context window, and is released under Apache 2.0.

  • Alibaba Qwen 3.8-27B for Coding & Multimodal Agentic Tasks

    The 27B-parameter Qwen 3.8-27B is a native vision-language model excelling in coding, multi-step agentic tasks, and multimodal understanding across text, images, and video. It features a 262K context window, extendable to ~1M, and achieved a 61.7 score on SWE-bench Pro.

Notes (1)
  • Simplified Deployment via SageMaker JumpStart

    AWS customers can deploy both Muse-Glimmer-30B and Qwen 3.8-27B with a few clicks through the SageMaker JumpStart model catalog in the SageMaker console. Deployment is also supported via the SageMaker Python SDK, enabling quick integration into existing AWS accounts.

Read the original announcement →

https://aws.amazon.com/about-aws/whats-new/2026/01/muse-glimmer-30b-qwen-3.8-27b-on-sagemaker-jumpstart/

Related releases