SambaNova Teams Up With Intel on Disaggregated Inference

2026-04-14 · Source: Big Data & AI News - EE Times · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Cloud Computing & IT Infrastructure, Robotics & Autonomous Systems · Depth: Advanced, short

Summary

SambaNova and Intel are partnering to develop a disaggregated inference solution specifically designed for serving agentic AI systems. This solution will integrate racks of SambaNova RDUs, Intel Xeon 6 CPUs, and existing data center GPUs. The architecture aims to address the high interactivity demands of agentic AI applications like code generation by optimizing different stages of LLM inference. SambaNova's approach uses Intel Xeon 6 CPUs for agentic tools and system orchestration, SN50 RDUs for the decode stage, and GPUs for the prefill stage. This setup contrasts with other architectures by handling all decode on RDUs and allowing for the use of GPUs from any vendor for prefill, with software interfaces like vLLM and NIXL facilitating standardization. The joint solution is expected to be available in the second half of 2026.

Key takeaway

For CTOs and VPs of Engineering evaluating infrastructure for agentic AI, this partnership offers a blueprint for a disaggregated inference solution that integrates specialized hardware. Your teams should consider how this architecture, which leverages existing GPU investments and optimizes CPU roles, could provide a streamlined, high-interactivity platform for next-generation AI applications. Plan for potential adoption by the second half of 2026.

Key insights

Disaggregated inference combines specialized hardware for agentic AI, optimizing performance and resource utilization.

Principles

• Interactivity drives demand for fast inference.
• CPUs connect AI agents to existing applications.

Method

SambaNova's disaggregated architecture uses Intel Xeon 6 CPUs for orchestration, SN50 RDUs for LLM decode, and existing GPUs for prefill, streamlining agentic AI workloads.

In practice

• Utilize existing GPU infrastructure for prefill.
• Employ Intel Xeon 6 CPUs for agentic tool orchestration.

Topics

• SambaNova
• Intel Xeon 6 CPUs
• Disaggregated Inference
• Agentic AI Systems
• LLM Inference

Best for: CTO, VP of Engineering/Data, Director of AI/ML, AI Architect, MLOps Engineer, AI Engineer

Related on AIssential

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• The Changing ASICs Landscape: the Shift Toward Chip Disaggregation — AI workloads drive ASICs towards system-specific, disaggregated architectures, demanding cross-domain collaboration and advanced packaging.
• SambaNova Abandons Intel Acquisition, Raises Funding Instead — SambaNova secured $350M funding and partnered with Intel, launching the SN50 chip for economic agentic AI inference.
• Another Giant Leap: The Rubin CPX Specialized Accelerator & Rack — Specialized hardware for prefill and decode phases of AI inference significantly optimizes cost and performance.
• The Inference Shift — AI's future compute landscape will diversify beyond GPUs, driven by distinct demands of "answer inference" and "agentic inference."
• ATOM: Unlocking Extreme AMD Instinct Inference with Software-Hardware Co-Optimization — ATOM is a ROCm-first, co-optimized inference engine for extreme LLM performance on AMD Instinct GPUs.

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Editorial summary, takeaway, and curation by AIssential. Original article published by Big Data & AI News - EE Times.