Concentrating intelligence

The first commercially viable models with 1-bit weights. Available in 8B, 4B, and 1.7B sizes, these models were engineered for robotics, real-time agents, and edge computing. They have a 14× smaller footprint than their full-precision counterparts, run 8× faster, and are 5× more energy efficient, while matching leading models at similar parameter counts on benchmarks. This results in over 10× the intelligence density of full-precision equivalents¹.

Ternary Bonsai models use {-1, 0, 1} weights to deliver a powerful balance between model quality and deployment efficiency. Available in 8B, 4B, and 1.7B sizes, these models have a 9× smaller footprint than full-precision counterparts and run roughly 5× faster, while delivering substantially stronger benchmark performance than most models at similar parameter counts. This creates a compelling tradeoff between capability and efficiency².