Intel Eyes SambaNova Systems to Strengthen Enterprise AI Position
Intel is reportedly in advanced discussions to acquire SambaNova Systems, a leading AI hardware and full-stack platform company, for approximately $1.6 billion, including debt. If completed, the deal could close as early as January 2026, though terms are still subject to change.
This valuation represents a significant discount from SambaNova’s $5 billion peak valuation during a 2021 funding round led by SoftBank. Reports indicate that SambaNova is also exploring other potential investors, making the deal not yet finalized. Intel’s CEO, Lip-Bu Tan, who also serves as SambaNova’s chairman, may expedite negotiations given his prior investment through his venture capital firm.
Why SambaNova Matters to Intel
SambaNova is a full-stack AI platform designed to challenge Nvidia’s dominance in the enterprise AI market. Key aspects of the company’s technology include:
- Reconfigurable Dataflow Unit (RDU) Chips: Custom chips optimized for high-performance AI inference and training, allowing enterprises to deploy large language models (LLMs) efficiently.
- SambaRack™ System: A complete solution combining RDU chips and SambaStack software, enabling on-premises or private cloud deployment.
- Inference Optimization: The SN40L chip focuses on inference workloads, offering high performance and power efficiency (tokens per watt) compared to general-purpose GPUs.
Intel has struggled to gain traction against Nvidia in AI accelerators. Acquiring SambaNova would provide a ready-made platform and proven technology to close that gap in enterprise AI workloads.
SambaNova’s Founding Team
SambaNova was founded in 2017 by experts from Stanford University:
- Kunle Olukotun (Co-Founder & Chief Technologist): A pioneer in chip multiprocessor (CMP) designs and professor at Stanford.
- Christopher Ré (Co-Founder): Associate professor specializing in data systems, machine learning, and large-scale AI systems.
- Rodrigo Liang (Co-Founder & CEO): Over two decades of enterprise system engineering experience at Sun Microsystems and Oracle, providing business and execution leadership.
Their mission: build a full-stack AI platform capable of handling complex, multi-modal enterprise workloads.
Intel’s AI Acquisition Strategy
Intel has a history of strategic AI-focused acquisitions to expand its technology portfolio:
| Acquisition | Year | Core Technology | Outcome/Integration |
|---|---|---|---|
| Mobileye | 2017 | ADAS and computer vision chips | Integral for autonomous vehicle computing; partial IPO in 2022 |
| Movidius | 2016 | Vision Processing Units (VPUs) for edge AI | Integrated into Intel CPUs as Neural Processing Units (NPUs) |
| Habana Labs | 2019 | Gaudi AI accelerators for data center AI | Key for Intel’s enterprise AI offerings; part of next-gen Jaguar Shores accelerators |
| SambaNova (Potential) | 2026 | RDU chips and full-stack enterprise AI system | Provides immediate, validated solution for enterprise inference and LLMs |
Intel’s acquisitions focus on two strategic pillars:
-
AI PC Initiative: Embedding AI acceleration into consumer processors using Movidius technology.
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Data Center Battle: Competing with Nvidia in the high-margin AI training and inference market, using Habana and potentially SambaNova hardware.
Strategic Significance of the Deal
Acquiring SambaNova would represent a major strategic leap for Intel:
- Immediate access to proven, high-performance AI hardware
- Entry into the enterprise AI inference market, where demand for LLM deployment is growing rapidly
- Potential to leverage existing internal connections to accelerate integration
- Strengthened ability to compete with Nvidia in a market currently dominated by its GPUs
Even at a discounted valuation, this move signals Intel’s commitment to securing top-tier AI technology and talent to remain competitive in the rapidly evolving AI hardware sector.
What’s Next
The deal is still under negotiation, and Intel has not confirmed any final terms. Market observers are watching closely, as the acquisition could reshape the enterprise AI landscape and position Intel more aggressively against Nvidia in both data center and AI enterprise markets.
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