Together AI just landed $800 million to prove that the cheapest way to run AI isn't always the most obvious one.
The San Francisco company said this week it closed an $800 million Series C at an $8.3 billion post-money valuation, with Aramco Ventures leading the round and Vista Equity Partners, General Catalyst, Emergence Capital, Nvidia, March Capital, Pegatron and S Ventures joining in. That price came in above the $7.5 billion valuation Investing.com had reported was under discussion just weeks earlier, and it arrived less than eighteen months after Together AI's $305 million Series B in February 2025. Across four rounds since its 2023 seed, the company has now raised roughly $1.3 billion.
You don't need to squint to see why Saudi Aramco's venture arm and Nvidia both wanted in. Together AI doesn't build its own frontier model. It runs other people's models, at scale, on infrastructure it controls, for customers who have grown tired of paying frontier-lab prices for work that doesn't need a frontier-lab model.
The numbers explain the pitch. Together AI said annual bookings crossed $1.15 billion last quarter, while open source model usage across the industry has tripled over the past twelve months. Customers including Cursor, Cognition and Decagon are running production workloads on models like DeepSeek, Nemotron, MiniMax and Kimi instead of closed alternatives, and the company says customers have reported cost savings ranging from 6x to 60x for equal or better performance. Decagon, the customer support AI company, has said it cut its own inference bill sixfold after making the switch.
For much of the last three years, the working assumption in Silicon Valley was that OpenAI and Anthropic would keep enough of a quality lead that enterprises would pay whatever it cost to stay on their APIs. That assumption is cracking. Chinese labs, DeepSeek chief among them, have shipped open-weight models that match or beat closed competitors on plenty of benchmarks, and Together AI's business exists to let companies use those models without running their own GPU clusters or negotiating their own chip supply.
Vipul Ved Prakash, who co-founded Together AI in 2022 after building the anti-spam system Vipul's Razor and the social analytics firm Topsy before Apple acquired it, has pitched the company around making frontier-grade AI economically accessible rather than reserved for customers that can absorb the biggest API bill. The new funding backs that pitch directly. Together AI says it plans to grow its infrastructure footprint roughly 50-fold over the next five years, a scale-up that only makes sense if demand for open models keeps compounding rather than leveling off.
Frankly, the investor list tells its own story. Aramco Ventures leading a Series C for an AI infrastructure company is a bet that compute capacity, not any single model, is where a lot of durable value may sit. Nvidia's participation is more direct. Every workload Together AI runs, no matter which open model sits on top of it, still needs chips underneath.
None of this means the closed labs are suddenly in trouble. OpenAI and Anthropic still set the pace on the hardest reasoning and coding tasks, and plenty of enterprises will keep paying a premium for that ceiling. But Together AI's bookings growth points to a real migration underway in the broader layer of enterprise AI workloads: support agents, coding assistants, internal chat tools, you name it. Those jobs don't always need the absolute frontier. They need something close to it at a fraction of the price.
That's the opening Cursor and Cognition already found when they moved workloads onto Together's infrastructure. It's the same opening Together AI just raised $800 million to widen.
Also read: Venice AI became a unicorn by promising to forget everything you tell it | Cisco is betting its whole workforce on AI agents while it cuts jobs | Meta Is Quietly Building a Business to Sell Its Leftover AI Computing Power
