Kev is a family of open decision models inspired by Jev and built on Qwen3.5 and Qwen3.8 foundations. It processes a document together with multiple typed questions and returns probabilities instead of generated prose. Supported question formats include yes-or-no, multiple choice, and ordered scoring. Checkpoints range from a compact 0.8B model for smaller hardware to a 27B version for high-end systems. The models include probability calibration and can run through CUDA, ROCm, or MLX depending on hardware. Kev exposes an API compatible with TypeSafe System One, allowing compatible clients to target a locally hosted server. Developers can also fine-tune models on their own labeled examples and deploy private HTTPS endpoints.
Features
- Yes-or-no, choice, and score decisions
- Calibrated probability outputs
- 0.8B through 27B model sizes
- CUDA, ROCm, and Apple MLX support
- TypeSafe System One-compatible API
- Custom fine-tuning and self-hosted deployment