LLMs

AWS introduced a Kubernetes-native Inference Gateway for SageMaker HyperPod that replaces round-robin load balancing with real-time, inference-signal-driven routing. Deployed as an EKS add-on, it uses Envoy to terminate HTTPS and a body-based router to direct requests to specific GPU pools by reading the model name from the request payload. This architecture enables single-endpoint serving for multiple models while reducing first-token latency by up to 82% and p99 TTFT by 97–98% in mixed-hardware scenarios.

• Zero client-side changes required; clients use a single private endpoint URL.
• Routes to correct GPU pools by parsing model name from request body.
• Deploys as an EKS managed add-on on existing HyperPod infrastructure.
• Cuts p99 TTFT by 97–98% in mixed-hardware and burst traffic scenarios.

The Pistis model family introduces 27B and 9B parameter multimodal LLMs built on Qwen3.6 and Qwen3.5. The team developed a novel post-training framework called IDRL that tightly integrates on-policy distillation and reinforcement learning. This approach alternates between the two objectives in a single loop to improve knowledge transfer compared to static or isolated methods.

• Pistis offers 27B and 9B multimodal variants based on Qwen3.6 and Qwen3.5.
• IDRL post-training alternates distillation and RL in one loop for better transfer.
• Outperforms static joint loss or isolated optimization of distillation/RL.
• Framework is designed to be general and scalable for future model development.
• Multimodal SFT is used to establish a strong foundation before IDRL training.

AWS has made OpenAI's GPT-6 Sol and GPT-6 Luna models generally available on Amazon Bedrock. Sol targets complex recurring tasks and software development, boasting significantly improved factuality over GPT-5.6. Luna serves as the high-efficiency option for volume-heavy operations like classification and routing. Both models support a 1 million token context window and are optimized for production-scale inference.

• GPT-6 Sol reduces factuality errors by roughly 50% compared to GPT-5.6 Sol.
• GPT-6 Luna is the go-to model for high-volume, focused tasks at lower cost.
• Both models support 1M token context windows for large input handling.
• Bedrock provides the security and scale needed for production deployments.

AWS GovCloud (US) has launched Anthropic’s Claude Opus 5.5, the latest iteration of the Opus family designed for complex coding and knowledge work. The model promises higher efficiency by completing tasks with fewer tokens and offering lower pricing, further reduced by cheaper cache reads. It features adaptive thinking capabilities and provides detailed reporting on its actions and findings to improve collaboration.

• Available in AWS GovCloud (US) for secure enterprise workloads
• Optimized for long-running coding and complex knowledge tasks
• Lower token usage and cost compared to Claude Opus 5
• Cheaper cache reads stack on top of base efficiency gains
• Features adaptive thinking and clear status reporting