Jane Street describes an ML estate with tens of thousands of high-end GPUs and more than one exabyte of current storage. Its page also links a tour of a Texas data center containing 4,032 liquid-cooled GPUs. These are firm-supplied figures, and the page does not establish a publication date, utilization rate, training spend or model size.
The more revealing detail is the job boundary: researchers and engineers work across market data, hyperparameter tuning, distributed-training debugging and analysis of production trades. Jane Street names LLMs, computer vision and reinforcement learning alongside training libraries and CUDA kernels, while saying it invents architectures and optimizations for trading. The scale makes data movement and reproducibility plausible constraints alongside raw computation, but the firm does not say which constraint dominates.
Jane Street also characterizes market data as mostly noise, regime-dependent and reflexive because its own actions affect the data it later models. The firm reports roughly $400 billion in daily filled dollars; that is trading flow, not revenue, assets or profit, and it cannot be assigned to any named ML method.