General Compute, an AI inference cloud startup, has secured a $400 million loan from Upper90, a tech investment firm. This significant financing deal marks a pivotal moment in the AI industry, as it may be the first instance of inference-specific chips being used as collateral. These chips are designed to run already-trained AI models efficiently and quickly, rather than the more expensive chips used to build the models in the first place.

The financing is a clear indication that markets are responding to concerns over the price of AI tools and tokens by shifting focus to infrastructure that runs open-source models more cheaply than the newest LLMs from frontier labs. This move is also a testament to the growing importance of open-source models in the AI landscape.

Founded by CEO Finn Puklowski, General Compute 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, unlike the general-purpose infrastructure offered by traditional hyperscalers like AWS or Azure. The company’s SN50 chips are designed for inference and are power-efficient, requiring no expensive water-cooling systems. This allows them to be deployed more quickly than GPUs across a larger variety of data centers.

General Compute claims that the new chips will provide 16 times faster inference than GPU-based clouds. However, the challenge lies in getting a large number of these chips, especially for a brand-new company. Upper90 co-founder and CEO Billy Libby, a former Goldman Sachs quantitative trader, has a playbook for this. In 2021, his firm financed GPU purchases by Crusoe, the energy-focused data center startup, which he believes was the first loan against the value of advanced chips.

Traditional lenders eschewed such deals at the time due to the risks and uncertainties surrounding GPU depreciation. However, as CoreWeave made chips-backed loans into a business model and then the basis of a blockbuster IPO, this kind of financing has become common. Libby notes that when Upper90 financed Nvidia GPUs as the first group to do that, the market was inefficient. They could really put together something as an early participant and get compensated for the risk.

Now that GPUs are comparatively well understood and perhaps over-bought, Upper90 is turning to companies like General Compute to ride the next wave of the AI boom. Libby believes that open-source models will be important and that the company went and looked for a player last year that was in inference. Not everyone needs a supercomputer, but they do need inference and AI.

This thesis has been growing stronger, with companies that provide access to open models, like OpenRouter and Fireworks, raising new rounds at huge valuations. New models like Kimi’s K3 have proven to compete with the latest releases from Anthropic and OpenAI on coding benchmarks. New chipmakers like Groq and Cerebras have drawn interest from acquirers and public markets alike.

General Compute’s ability to access chips outside of 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, compute providers that aren’t locked into Nvidia deals may have an advantage in providing cost-efficient inference.

There are a bunch of chips that are starting to scale that have amazing [total cost of ownership], or that can operate much faster than Nvidia, but there’s not too many buyers for them. By getting together with Upper90, this is not just, ‘a cool startup got some money to buy some compute.’ Like, this is the first signal of capital organizing itself and the fragmenting of Nvidia’s monopolistic dominance.