Amazon SageMaker AI now supports serverless model customization for NVIDIA Nemotron 3.5 Lightning
Amazon SageMaker AI now supports serverless model customization for the NVIDIA Nemotron 3.5 Lightning model using supervised fine-tuning (SFT), Direct Preference Optimization (DPO), and reinforcement fine-tuning (RFT).
Also shipped Sep 16, 2026AWS in September 2026 →
BigQuery migration lineage service enters preview
The migration lineage service visualizes data flow and connections in a source database to help plan a BigQuery data warehouse migration.
Cortex Agents object enhancements (General availability)
The following Cortex Agents object enhancements are now generally available:
Include and exclude per-user quota users by name (General availability)
Per-user quotas now accept individual user names, so you can add or remove specific users alongside the quota's tag scope. INCLUDE_USERS is new and takes user names directly, and EXCLUDE_USERS accepts a 'USER' argument alongside its existing 'TAG' form:
Weekly per-user quota limits (General availability)
Per-user quotas now support a weekly credit limit alongside the existing monthly and daily limits. Pass 'WEEKLY' as the cycle argument to SET_PER_USER_LIMIT :
Anthropic models will be removed from AWS GovCloud IL5 workspaces
On September 19, 2026, Anthropic models will be removed from Databricks on AWS GovCloud and AWS GovCloud DoD workspaces that have the DoD Impact Level 5 (IL5) compliance standard selected. After this date, IL5 workspaces can't create or use endpoints that serve Anthropic models.
Unity Gateway API and developer tools are generally available
The Unity Gateway API for managing model services, model provider services, and MCP services is now generally available, with create, read, update, list, and delete support across Databricks developer tools: Terraform provider : 1.132.0 and later Databricks CLI : v1.17.0 and later Python SDK : databricks-sdk 0.136.0 and later Go SDK : databricks-sdk-go...
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Amazon SageMaker AI now supports instance preference lists for training and processing jobs
Today, Amazon SageMaker AI announces instance preference lists for training and processing jobs, making it easier and faster to find compute capacity for your workloads. Many AI training, fine-tuning, and data processing workloads run comparably well on any of several instance types or sizes.
Qwen3.6-35B-A3B-NVFP4 and Wan2.1-T2V-1.3B-Diffusers models now available on Amazon SageMaker JumpStart
NVIDIA's Qwen3.6-35B-A3B-NVFP4 and Alibaba's Wan2.1-T2V-1.3B-Diffusers models are now available on Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers.
Ministral-3-3B-Instruct-2512 and Ministral-3-8B-Instruct-2512 models now available on Amazon SageMaker JumpStart
Mistral AI's Ministral-3-3B-Instruct-2512 and Ministral-3-8B-Instruct-2512 models are now available on Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers.
Gemma-4-31B-it-assistant and Gemma-4-31B-IT-NVFP4 models now available on Amazon SageMaker JumpStart
Google DeepMind's Gemma-4-31B-it-assistant and NVIDIA's Gemma-4-31B-IT-NVFP4 models are now available on Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers.
granite-speech-4.1-2b, kanana-2-30b-a3b-instruct, and OpenFold3 models now available on Amazon SageMaker JumpStart
BM's granite-speech-4.1-2b, Kakao's kanana-2-30b-a3b-instruct, and the OpenFold Consortium's OpenFold3 models are now available on Amazon SageMaker JumpStart, expanding the portfolio of foundation models available to AWS customers.
Amazon SageMaker HyperPod now supports model caching for faster inference autoscaling and reduced cold starts
Amazon SageMaker HyperPod now supports model caching, an inference optimization that pre-loads model weights and container images onto cluster nodes so pods start in seconds instead of minutes. When running LLM inference at scale for workloads like chat assistants, agentic pipelines, RAG, and document analysis, cold start is a real bottleneck.
Amazon SageMaker Unified Studio now supports ODBC connections for Microsoft Power BI and other analytics tools
Amazon SageMaker Unified Studio now supports ODBC connections, so data users can connect Microsoft Power BI and other ODBC-compatible tools directly to governed data in SageMaker Unified Studio projects using the Amazon Athena ODBC driver.
Amazon SageMaker HyperPod Inference Gateway for scalable LLM inference
Amazon SageMaker HyperPod Inference Gateway is a Kubernetes-native, GPU-aware routing system that deploys as a single EKS managed add-on on existing SageMaker HyperPod infrastructure with zero application changes.