Red Hat and AWS accelerate hybrid AI inference with new chip integrations and production push

Red Hat and Amazon Web Services have expanded their collaboration to make generative AI inference more efficient across hybrid cloud environments, leveraging AWS’s Trainium and Inferentia chips and supporting an industry shift towards custom silicon for AI workloads.

Red Hat said it has expanded its collaboration with Amazon Web Services to let organisations run generative AI inference on AWS using Red Hat AI alongside AWS’s Trainium and Inferentia chips. The company claims the effort will let enterprises move AI workloads across hybrid cloud environments with “enhanced efficiency and flexibility,” and it announced that an AWS Neuron community operator is available in the Red Hat OpenShift OperatorHub while Red Hat AI Inference Server support for AWS chips is expected in developer preview in January 2026. [^[1]^](https://www.businesswire.com/news/home/20251202946791/en/Red-Hat-to-Deliver-Enhanced-AI-Inference-Across-AWS?feedref=JjAwJuNHiystnCoBq_hl-bV7DTIYheT0D-1vT4_bKFzt_EW40VMdK6eG-WLfRGUE1fJraLPL1g6AeUGJlCTYs7Oafol48Kkc8KJgZoTHgMu0w8LYSbRdYOj2VdwnuKwa)[^[2]^](https://www.redhat.com/en/about/press-releases/red-hat-deliver-enhanced-ai-inference-across-aws)

The announcement frames the work as part of a broader drive to offer an “any model, any hardware” approach that optimises inference for cost and latency compared with current GPU-based instances. Red Hat described the initiative as combining its OpenShift and AI tooling with AWS purpose-built accelerators to provide a common inference layer for large language models and other gen AI workloads. [^[1]^](https://www.businesswire.com/news/home/20251202946791/en/Red-Hat-to-Deliver-Enhanced-AI-Inference-Across-AWS?feedref=JjAwJuNHiystnCoBq_hl-bV7DTIYheT0D-1vT4_bKFzt_EW40VMdK6eG-WLfRGUE1fJraLPL1g6AeUGJlCTYs7Oafol48Kkc8KJgZoTHgMu0w8LYSbRdYOj2VdwnuKwa)[^[2]^](https://www.redhat.com/en/about/press-releases/red-hat-deliver-enhanced-ai-inference-across-aws)[^[4]^](https://developers.redhat.com/articles/2025/12/02/cost-effective-ai-workloads-openshift-aws-neuron-operator)

Red Hat included an industry forecast in its statement, citing IDC to underline demand for custom silicon such as ARM and AI-specific chips. The company said such trends are pushing organisations to reassess their infrastructure to balance performance and cost as they move from experimentation to production. [^[1]^](https://www.businesswire.com/news/home/20251202946791/en/Red-Hat-to-Deliver-Enhanced-AI-Inference-Across-AWS?feedref=JjAwJuNHiystnCoBq_hl-bV7DTIYheT0D-1vT4_bKFzt_EW40VMdK6eG-WLfRGUE1fJraLPL1g6AeUGJlCTYs7Oafol48Kkc8KJgZoTHgMu0w8LYSbRdYOj2VdwnuKwa)

The firm quoted senior executives to explain the partnership’s rationale. “By enabling our enterprise-grade Red Hat AI Inference Server, built on the innovative vLLM framework, with AWS AI chips, we’re empowering organizations to deploy and scale AI workloads with enhanced efficiency and flexibility,” Joe Fernandes, vice president and general manager of Red Hat’s AI business unit, said in the company’s announcement. Colin Brace of AWS described Trainium and Inferentia as engineered to deliver “exceptional performance, cost efficiency, and operational choice” for mission-critical AI workloads. [^[1]^](https://www.businesswire.com/news/home/20251202946791/en/Red-Hat-to-Deliver-Enhanced-AI-Inference-Across-AWS?feedref=JjAwJuNHiystnCoBq_hl-bV7DTIYheT0D-1vT4_bKFzt_EW40VMdK6eG-WLfRGUE1fJraLPL1g6AeUGJlCTYs7Oafol48Kkc8KJgZoTHgMu0w8LYSbRdYOj2VdwnuKwa)

External observers note the move fits into a wider AWS strategy to push its own silicon into the AI stack. AWS has been promoting Trainium and Inferentia through partnerships and initiatives that include training agreements with major model providers and researcher credit programmes designed to encourage adoption of its chips. Those activities underline AWS’s aim to present an alternative to GPU-first deployments, particularly for inference and certain training workloads. [^[5]^](https://www.aboutamazon.com/news/aws/what-you-need-to-know-about-the-aws-ai-chips-powering-amazons-partnership-with-anthropic/)[^[6]^](https://apnews.com/article/7a5764907e8cf0c23117be9c710e9f6a)[^[7]^](https://www.reuters.com/technology/artificial-intelligence/amazon-offers-free-computing-power-ai-researchers-aiming-challenge-nvidia-2024-11-12/)

Technical coverage of the operator integration says the AWS Neuron operator automates kernel module deployment, device plugin management, scheduling and telemetry on OpenShift clusters, which could simplify the operational burden for enterprises seeking to use AWS accelerators on hybrid platforms. Red Hat and AWS both emphasised support for mixed container and VM environments as part of their broader hybrid-cloud collaboration. Industry analysts cited by the company say cost efficiency is increasingly a deciding factor as organisations scale AI inference. [^[4]^](https://developers.redhat.com/articles/2025/12/02/cost-effective-ai-workloads-openshift-aws-neuron-operator)[^[3]^](https://www.redhat.com/en/about/press-releases/red-hat-signs-strategic-collaboration-agreement-aws-propel-virtualization-and-ai-innovation-across-hybrid-cloud)[^[1]^](https://www.businesswire.com/news/home/20251202946791/en/Red-Hat-to-Deliver-Enhanced-AI-Inference-Across-AWS?feedref=JjAwJuNHiystnCoBq_hl-bV7DTIYheT0D-1vT4_bKFzt_EW40VMdK6eG-WLfRGUE1fJraLPL1g6AeUGJlCTYs7Oafol48Kkc8KJgZoTHgMu0w8LYSbRdYOj2VdwnuKwa)

While Red Hat and AWS present the work as a production-ready path, independent observers caution that real-world migration of LLM workloads often requires substantial engineering work and benchmarking across models, frameworks and datasets before promised efficiency gains materialise. The companies position the offering as a route from pilot to production, but customers will need to validate performance claims against their own workloads and governance requirements. [^[1]^](https://www.businesswire.com/news/home/20251202946791/en/Red-Hat-to-Deliver-Enhanced-AI-Inference-Across-AWS?feedref=JjAwJuNHiystnCoBq_hl-bV7DTIYheT0D-1vT4_bKFzt_EW40VMdK6eG-WLfRGUE1fJraLPL1g6AeUGJlCTYs7Oafol48Kkc8KJgZoTHgMu0w8LYSbRdYOj2VdwnuKwa)[^[4]^](https://developers.redhat.com/articles/2025/12/02/cost-effective-ai-workloads-openshift-aws-neuron-operator)[^[7]^](https://www.reuters.com/technology/artificial-intelligence/amazon-offers-free-computing-power-ai-researchers-aiming-challenge-nvidia-2024-11-12/)

📌 Reference Map:

##Reference Map:

• [^[1]^](https://www.businesswire.com/news/home/20251202946791/en/Red-Hat-to-Deliver-Enhanced-AI-Inference-Across-AWS?feedref=JjAwJuNHiystnCoBq_hl-bV7DTIYheT0D-1vT4_bKFzt_EW40VMdK6eG-WLfRGUE1fJraLPL1g6AeUGJlCTYs7Oafol48Kkc8KJgZoTHgMu0w8LYSbRdYOj2VdwnuKwa) (Business Wire / Red Hat press release) – Paragraph 1, Paragraph 2, Paragraph 3, Paragraph 4, Paragraph 6, Paragraph 7
• [^[2]^](https://www.redhat.com/en/about/press-releases/red-hat-deliver-enhanced-ai-inference-across-aws) (Red Hat press page) – Paragraph 1, Paragraph 2
• [^[3]^](https://www.redhat.com/en/about/press-releases/red-hat-signs-strategic-collaboration-agreement-aws-propel-virtualization-and-ai-innovation-across-hybrid-cloud) (Red Hat strategic collaboration press page) – Paragraph 6
• [^[4]^](https://developers.redhat.com/articles/2025/12/02/cost-effective-ai-workloads-openshift-aws-neuron-operator) (Red Hat developer article) – Paragraph 2, Paragraph 6, Paragraph 7
• [^[5]^](https://www.aboutamazon.com/news/aws/what-you-need-to-know-about-the-aws-ai-chips-powering-amazons-partnership-with-anthropic/) (About Amazon / AWS–Anthropic coverage) – Paragraph 5
• [^[6]^](https://apnews.com/article/7a5764907e8cf0c23117be9c710e9f6a) (AP News on Amazon–Anthropic investment) – Paragraph 5
• [^[7]^](https://www.reuters.com/technology/artificial-intelligence/amazon-offers-free-computing-power-ai-researchers-aiming-challenge-nvidia-2024-11-12/) (Reuters on AWS researcher credits) – Paragraph 5, Paragraph 7

Source: Fuse Wire Services