Try the Jev Model by TypeSafe in a playground or via API
Foundation model for mobile, wearables, robots, smart home, automotive and microcontrollers
Stage
Startup
Startup
Founded
2026
Not given
Based in
Not given
Not given
Pricing model
Freemium
Open source
Pricing
Free: 20 welcome credits for new accounts. Token packs: 15M input tokens at $0.600/1M ($9 one-time), 75M tokens at $0.520/1M ($39 one-time), 200M tokens at $0.380/1M ($76 one-time), 600M tokens at $0.283/1M ($170 one-time). Annual subscriptions available at 50% discount. Output tokens are free.
Not given
Key features
Yes/No probability questions
Choice questions with confidence
Score questions with rating levels
Browser-based playground
RESTful API with TypeSafe-compatible format
Batch processing tools
Support for images and video (Jev-Omni variant)
Multiple language support
Calibrated confidence scores
Parallel question processing
Tool calling with function selection and argument filling
Structured extraction with guaranteed JSON parsing
Text embeddings for local semantic search and matching
Confidence scoring for routing and gating calls
Laddered subnetwork architecture from 2 to 20 layers
LoRA fine-tuning support for customization
400-4k tokens per second inference speed on Raspberry Pi 5
Python package with pip install and Hugging Face distribution
What makes it different
System One model optimized for structured decisions, not text generation
Calibrated probabilities and confidence scores built into every response type
Fast responses at approximately 0.5 seconds
Independently operated by Jev AI, separate from TypeSafe
Output tokens are free, billing only for input
Beats models 10x its size on mobile tool calling benchmarks
Matches models 2-3x larger on structured extraction tasks
Entire model in a single 8-29 MB binary for tiny devices
Simple Attention Network architecture uses 2x fewer MFLOPs than transformers
Fine-tuned subnetworks outperform larger models like DeepSeek V4 Flash
Jev AI