Queue and run experiments on one GPU with a minimal GPU-aware spooler

Queue and run experiments on one GPU with a minimal GPU-aware spooler targets a $740M = 2,000,000 prosumer and small-team GPU users × $370 average ACV total addressable market with medium saturation and a year-over-year growth rate of 15% YoY — developer tools and ML infra consumption is growing as more experimentation moves to local and hybrid setups (industry reports and community activity indicate roughly mid- to high-teens growth).

Key trends driving demand: Local-first ML experimentation — more developers run models on local GPUs before scaling to cloud, increasing demand for local tooling that manages GPU contention.; Developer tooling preference for single-purpose, composable tools — teams prefer small, easy-to-install tools for specific workflows instead of monolithic platforms.; Rising prosumer GPU ownership — falling GPU prices and more powerful consumer hardware make single-node GPU workflows common among hobbyists and small teams.; Open-source + paid-support monetization — many developer tools succeed as open-source with a paid layer for advanced features and support, enabling fast adoption and monetization..