A new category of AI models that pick answers instead of generating them launched in September 2026 and immediately spawned dozens of competitors. The article cuts through the noise by laying out practical criteria for choosing which decision model to use in production rather than tracking which specific model is "best."

• Jev launched September 15 and hit massive adoption (13% of Vercel's paid customers integrated it within a day), but within two weeks Amazon, OpenAI, Cloudflare, and others shipped competing models with different tradeoffs.
• DecideBench, an independent benchmark testing 400 multiple-choice decisions across eight task families, shows Jev at 98% accuracy for $32 per million tasks, but smaller open models like Laya are 35-59% accurate and much faster—accuracy-speed tradeoffs matter depending on your use case.
• The real decision criteria are deployment location (hosted vs. self-hosted), input types (text-only vs. image support), latency requirements, cost at your actual volume, and API compatibility for future switching—not which model has the best benchmark score.

TypeSafe AI's decision model Jev autonomously completed Pokémon Red by reading game memory, evaluating legal moves with game facts, and making every decision—from battle tactics to menu choices—over 37 hours and 16,150 decisions. The entire run cost $1.65 in API tokens, with full source code and setup instructions open on GitHub.

• Jev made every game decision (battles, catching, team swaps, navigation) based on legal options and contextual facts, while the harness only handled emulation and button presses—no cheats or memory writes.
• The project cost $1.65 total at $0.042 per million input tokens, with typical calls around 1,200 tokens and median decision time of 0.4 seconds; the full run consumed ~39.2M input tokens.
• All code is open-source (GPL-2.0) and reproducible locally with your own legally obtained Pokémon Red ROM, Node 20+, and macOS or Linux—no Nintendo assets or ROMs are distributed.