Features
Local inference on Apple Silicon (M-series chips)
Model conversion and compression
Quantization schemes co-designed with architecture
Hardware-aware tensor operation optimization
Batch size = 1 inference engine
Real-time decoding for interactive AI
Apple device automation integration
Models library for pre-optimized models
Sparse buffers for KV cache (June 2026)
New quantization method for speed-quality frontier (June 2026)
One-command install on macOS, Linux, Windows
Run hundreds of open models locally
MLX engine for Apple Silicon (faster, less memory)
GGUF model support via llama.cpp (Ollama 0.30)
NVIDIA Nemotron 3 Ultra for high-throughput reasoning
Cloud scaling with Free, Pro, Max tiers
Run multiple cloud models in parallel (1, 3, 10)
Web-enabled cloud agents for real-time info retrieval
Fully offline operation for mission-critical work
Data never used for training; privacy-first design
CLI tool with model management and configuration
REST API for building AI applications
Upload and share private models (Pro and above)
40,000+ community integrations
Desktop app for macOS, Linux, Windows
