Features
Native Apple Silicon ML framework (M1-M5)
Zero-allocation MLX bridge
Custom Metal and ANE acceleration paths
TurboQuant KV cache compression (4-6x)
Long-context discontinuous batch serving
Multi-Mac distributed training over Thunderbolt
LoRA/QLoRA/DoRA fine-tuning
Full-parameter pretraining
SFT, GRPO/DAPO, RLKD, distillation
20-workspace terminal TUI
19-screen Tauri desktop GUI
OpenAI/Anthropic-compatible serving API
Model quantization (GGUF, MLX, etc.)
Model merging (SLERP, TIES, DARE, Fisher, RegMean)
GPU compute with NVIDIA Vera Rubin, GB300, B300, Blackwell, Hopper, Ada Lovelace
CPU compute and bare metal servers
AI Object Storage with zero egress migration
Distributed file storage and dedicated VAST Storage
Backblaze multi-exabyte storage integration
Managed Kubernetes with automated provisioning
SUNK runtime acceleration for reinforcement learning
MLPerf v5.0 leading training and inference performance
CoreWeave Sandbox for model and agent development
Mission Control for observability, security, fleet lifecycle
Tensorizer for model optimization
Cluster Health Management and monitoring
Node lifecycle controller for automated node management
High-performance networking for cluster scale-out
Capacity plans with guaranteed compute and pricing
