Why the first GPU financiers are turning to inference chips in a $400 million deal

General Compute, an AI-inference cloud startup, has secured a $400 million loan from Upper90, a technology investment firm. It could be the first deal to offer inference-specific chips as collateral: chips built to run already-trained AI models quickly and efficiently, rather than the more expensive chips used to build the models in the first place.

The funding is the latest signal that markets are responding to concerns about the price of AI tools and tokens by turning to infrastructure that runs open-source models cheaper than the latest LLMs from frontier labs.

General Compute, founded by CEO Finn Puklowski, raised a $15 million seed round in May to build an inference neocloud around silicon from SambaNova, an Intel-backed chipmaker. (Neoclouds are purpose-built for AI workloads, as opposed to the general infrastructure offered by traditional hyperscalers like AWS or Azure.)

The company’s SN50 chips are designed for inference. They are energy efficient and do not require expensive water cooling systems, meaning they can be deployed more quickly than GPUs in a wider variety of data centers. General Compute says the new chips will provide sixteen times faster inference than GPU-based clouds.

The challenge is getting a lot of these chips, especially if you’re a brand new company.

Upper90 co-founder and CEO Billy Libby, a former Goldman Sachs quantitative trader, had a playbook for this: In 2021, his company financed GPU purchases by Crusoe, the energy-focused data center startup, which he said was the first loan against the value of cutting-edge chips.

Traditional lenders shied away from such deals at the time because of the risks and uncertainties surrounding GPU depreciation. But as CoreWeave turned chip-backed lending into a business model and then the foundation of a successful IPO, this type of financing has become commonplace.

“When we funded Nvidia GPUs as the first group to do so, the market was inefficient,” Libby told TechCrunch. “We could really put something together as an early participant, and get some kind of compensation for the risk.”

Now that GPUs are relatively well understood and perhaps overbought, Upper90 is turning to companies like General Compute to ride the next wave of the AI ​​boom. “We think open source models will be important, and last year we started looking for an inference player,” Libby said. “Everyone doesn’t need a supercomputer, but they do need inference and AI.”

That thesis has become increasingly stronger as companies that provide access to open models, such as OpenRouter and Fireworks, launch new rounds at huge valuations. New models like Kimi’s K3, as recently as this week, have proven to compete with the latest releases from Anthropic and OpenAI in coding benchmarks. And new chipmakers like Groq and Cerebras have attracted interest from both acquirers and public markets.

General Compute’s ability to access chips outside Nvidia’s ecosystem matters for the same reason. TensorWave, another AI infrastructure company, is making a similar bet on a partnership with AMD. As more alternatives to Nvidia emerge, computer providers not tied to Nvidia deals may have an advantage in offering cost-efficient inference.

“There are a number of chips that are starting to scale up and are delivering great performance [total cost of ownership]’, or that could work much faster than Nvidia, but there aren’t as many buyers for it,’ Puklowski said.’ By partnering with Upper90, this isn’t just ‘some cool startup got some money to buy some computer.’ For example, this is the first signal that capital is organizing itself and the fragmentation of Nvidia’s monopolistic dominance.”