High-cost GPU time for small ML runs — token-priced shared GPU inference

High-cost GPU time for small ML runs — token-priced shared GPU inference targets a $24.0B = 6M developers & SMBs x $4.0K ACV (annual GPU/inference spend & related tooling) total addressable market with medium saturation and a year-over-year growth rate of 25%+ growth in cloud GPU spend and inference services driven by LLM adoption.

Key trends driving demand: LLM democratization -- more individual devs and creators need occasional inference without long-term infrastructure.; Spot/preemptible GPU availability -- cloud providers and marketplaces offer cheaper transient capacity enabling low-cost pooling.; Serverless & inference optimization tooling -- mature runtimes (Triton, ONNX) and containerization speed time-to-market.; Pay-per-usage billing expectations -- users are accustomed to token/second billing from API-first LLM providers..