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Key Points
- AI chip startup SambaNova just raised $1 billion from investors, valuing it at $11 billion, following a February fundraising round of $350 million.
- SambaNova’s valuation trajectory resembles that of Cerebras Systems, which went public in May and was one of the hottest IPOs of 2026.
- A SambaNova IPO is no guarantee, and the company has already fielded interest from various companies, including its partner and investor Intel.
Artificial intelligence (“AI”) chip startup SambaNova just raised $1 billion from investors, giving it a total valuation of $11 billion. The private company makes chips for AI inference, and it seems to be following in the footsteps of Cerebras Systems (CBRS), which conducted the largest semiconductor initial public offering (“IPO”) ever in May.
That IPO was one of the most popular in years – will SambaNova be one of the next big IPOs?
SambaNova bills itself as “the world’s fastest AI inference platform,” and like Cerebras, it builds AI chips that process inference workloads. Inference is the process of generating AI chatbot outputs based on user inputs, and it’s becoming a larger part of overall AI workloads.
SambaNova’s latest chip is called the SN50, and it’s used in servers installed in AI data centers. The company says its chip runs the largest AI models with trillions of parameters, and it fits them on a single server rack, helping models run faster. SambaNova says the SN50 delivers better performance than industry juggernaut Nvidia’s (NVDA) B200 chips.
The firm has signed up some well-known clients for the SN50, which is expected to roll out by the end of the year. As part of its most recent fundraising news, SambaNova revealed that JPMorgan Chase (JPM) signed a deal to deploy its SN40L and SN50 systems for their on-premises AI inference. Tech investor SoftBank (SFTBY), however, will be the first customer to put the SN50 into use.
SambaNova also identified Saudi Aramco, Meta Platforms (META), and Intel (INTC) as clients.
But Intel is also an investor in SambaNova, as is Intel CEO Lip-Bu Tan, who has been the executive chairman of SambaNova since 2017. Intel participated in the latest fundraising round as well as in SambaNova’s $350 million round in February. The two companies announced a multiyear deal earlier this year that would develop AI inference based on Intel’s Xeon semiconductor.
SambaNova said its recent capital raise would help grow its business and secure its supply chain, as waves of chip companies are driving demand higher. Chipmakers are rushing to build out alternatives to challenge Nvidia’s dominance and capture a piece of its hefty margins.
AI Chip Companies Targeting Nvidia
Nvidia seems to be the target of every AI chip company these days. A range of new startups has Nvidia – and its incredibly wide 65.6% operating margin – in their crosshairs, as the AI industry increasingly shifts its workflows from training models to inference.
AI workloads are quickly moving to inference. Deloitte estimates that inference workloads will make up about two-thirds of all AI workloads in 2026, up from just half in 2025. That number has climbed from a mere 20% a few years ago, and it could rise to 80% by 2027, says McKinsey.
AI chip companies such as SambaNova are looking to deploy solutions that deliver inference quickly and cost-effectively, so users aren’t waiting around for models to process their tasks.
Part of SambaNova’s solution to improving efficiency is to bring inference in-house, as shown in its recent deal with JPMorgan Chase. It’s deploying AI servers at data centers owned by specific business clients, a move that also helps improve data security, since the data is controlled by the company itself rather than by a third-party AI provider or an AI lab.
Other AI chip companies, such as Cerebras Systems, have taken different tracks to compete in the AI inference race. Cerebras produces wafer-scale chips about the size of a plate that process inference workloads faster than Nvidia’s graphics processing units, it says. Cerebras bills itself as the “maker of the world’s fastest AI infrastructure.”
For example, Cerebras’ WSE-3 chip packs on a whopping 4 million transistors divided across 900,000 cores and 44 gigabytes of memory. The large supply of memory means it can run AI models on the chip, sidestepping the slower process of moving them off the chip.
Billions of dollars continue to flow into the AI chip sector as well as into memory chips, with South Korea’s SK Hynix (SKHY) recently completing a secondary listing on Nasdaq.
SambaNova IPO: What to Expect and How Soon It Could Happen
SambaNova is considering an IPO in 2027 and is leaning toward listing on the U.S. market, according to co-founder and CEO Rodrigo Liang. Of course, any IPO depends on factors beyond the company’s control, such as the state of the market itself. If the market starts to get cold or the AI bubble bursts, it will be tough for private companies to debut.
But in a hot sector such as AI chips, a company can reach the public markets much faster than expected. For example, consider Cerebras, which conducted its own IPO in May.
- In September 2025, Cerebras raised $1.1 billion at an $8.1 billion valuation.
- In February 2026, Cerebras raised $1 billion at a $23 billion valuation.
- In May, Cerebras kept repricing its IPO higher, ultimately going public at an IPO valuation of around $56 billion.
So, in a period of eight months or so, Cerebras went from a lower valuation than SambaNova’s ($8.1 billion versus $11 billion) to an IPO that multiplied its market capitalization some 7 times. The market moved quickly on Cerebras, and it could do the same for SambaNova.
Of course, it’s always possible that another semiconductor company makes a bid for the firm. SambaNova’s CEO has been noncommittal on whether the company will actually hold an IPO.
In fact, Intel was already in talks last year to acquire the company for $1.6 billion, including debt, according to Bloomberg. The recent capital raise already seems to put that figure well below what the company can fetch in private markets – and maybe soon in the public market.
Regards,
James Royal, PhD
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