Stock Markets July 1, 2026 12:06 PM

Together AI Secures $800 Million Series C, Valuation Climbs to $8.3 Billion

Investment led by Aramco Ventures accelerates startup’s push into inference and larger-scale infrastructure for open-source AI models

By Caleb Monroe
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Together AI announced an $800 million Series C funding round led by Aramco Ventures that lifts the company's valuation to $8.3 billion. The 2022-founded startup, which helps enterprises train and run AI workloads on open models at lower cost than closed systems, said the capital will support expansion into inference services and a large build-out of computing capacity and infrastructure.

Together AI Secures $800 Million Series C, Valuation Climbs to $8.3 Billion
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Key Points

  • Together AI raised $800 million in a Series C round led by Aramco Ventures, valuing the company at $8.3 billion.
  • The startup’s platform supports training and running AI workloads on open models such as DeepSeek, MiniMax and Kimi, and the company plans to expand into inference services.
  • Reported annual bookings topped $1.15 billion last quarter; Together AI expects to expand computing capacity and infrastructure roughly 50-fold over the next five years. Sectors impacted include cloud infrastructure, enterprise AI services and software vendors.

Together AI said on Wednesday it has closed an $800 million Series C financing round led by Aramco Ventures, a deal that more than doubles the artificial intelligence firm's valuation to $8.3 billion.

Launched in 2022, Together AI offers a platform that enables companies to train and operate AI workloads using open models such as DeepSeek, MiniMax and Kimi, positioning itself as a lower-cost alternative to closed systems.

The Series C brought participation from a range of investors including Vista Equity Partners, General Catalyst, Emergence Capital, Nvidia, Salesforce Ventures, March Capital, Pegatron and SentinelOne’s S Ventures. Together AI said it will direct the new capital toward widening its product set while moving further into inference - the runtime process of executing trained AI models.

"The future of AI won’t be owned by a few companies. It will be built by millions of developers and businesses, and open-source models are making that possible," Together AI CEO Vipul Ved Prakash said.

Financial indicators offered by the company underscore rapid growth. Together AI reported that annual bookings exceeded $1.15 billion in the last quarter, a figure the company tied to increased usage of open-source models. The startup counts customers including Cursor, Cognition and Decagon.

The new valuation represents a sizable jump from the $3.3 billion valuation Together AI received in a February 2025 funding round led by General Catalyst. That February figure itself had topped the earlier $1.25 billion valuation recorded in March 2024.

Alongside product expansion, Together AI provided an operational forecast: the company expects its computing capacity and infrastructure to grow by roughly 50-fold over the next five years.


Taken together, the funding round and the company's performance metrics indicate both investor confidence and an aggressive scaling plan focused on inference and infrastructure. The participation of strategic investors and technology companies signals support for open-model approaches and for platforms that promise cost efficiencies relative to closed AI systems.

While Together AI framed the new capital as a means to broaden product offerings and service capabilities, the company also highlighted the commercial momentum it has gained from rising open-source model adoption and a high level of bookings.

Risks

  • Execution risk tied to the plan to expand computing capacity and infrastructure roughly 50-fold over five years - this affects cloud infrastructure providers and enterprises relying on scalable inference services.
  • Dependence on rising open-source model usage to sustain bookings and growth - a shift away from open-source adoption could affect demand for Together AI’s platform, impacting AI software and services markets.
  • Uncertainty in moving into inference as a provider - transitioning from training and tooling to runtime service delivery involves operational and competitive risks for enterprise AI and cloud service sectors.

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