Chips and Semiconductors

Tenstorrent raises $1.5 billion and lifts valuation to $6.2 billion to support AI chips

Inference chip startup Tenstorrent has raised $1.5 billion in funding, lifting its valuation to $6.2 billion to scale its chips dedicated to open-weight models and avoid acquisition.

2026-10-19
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certi.news Editorial Team
Tenstorrent raises $1.5 billion and lifts valuation to $6.2 billion to support AI chips

Tenstorrent, the AI processor startup focused on inference operations, has successfully raised a new funding round of $1.5 billion, bringing its total market valuation to $6.2 billion. This move comes about five months after reports emerged that the company, led by prominent engineer Jim Keller, had received potential acquisition offers from major companies such as Intel and Qualcomm with estimates reaching up to $5 billion.

Independence and expanding inference chip capabilities

The company confirmed that its decision tilted toward maintaining its independence rather than accepting acquisition offers, relying on the success of its Galaxy servers in efficiently running DeepSeek models. The new funding, which doubled the company's valuation compared to late 2024 when it stood at $2.6 billion, will be directed toward developing and scaling the production of chips specifically designed to power open-weight AI models and video generation technologies.

Fierce competition in the AI hardware market

The new funding round was led by Trace Capital, a new investment firm launched by Quiet Capital partner Ben Mahdavi, alongside Innovation X. The list of investors also included prominent names such as Cadence Ventures, Eclipse, Fidelity, SanDisk, and T. Rowe Price.

What changes practically?

This massive funding reflects a strategic shift in the AI hardware market, where startups with promising technologies prefer to remain independent and compete directly thanks to financial investor support rather than merging under the umbrella of tech giants. Furthermore, Tenstorrent's focus on open-weight models represents a direct response to the ongoing shift in the adoption of open models such as DeepSeek and its competitors across enterprises and organizations.

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