Performance
Hardware-conscious software extracts more inference performance from workstations and local multi-GPU systems.
Independent nonprofit Open source
Intelligence,
within reach.
We develop open kernels, tools, benchmarks, and research for AI inference on hardware you control.
Research
Kernels
Tools
Benchmarks
01 Open source
02 Local-first
03 Hardware-aware
04 Community-led
01 Why local
Local infrastructure should run capable AI.
Local AI improves privacy, ownership, access, and room to experiment. We build software and publish research for demanding inference workloads.
Evidence
Reproducible benchmarks and practical research support configuration, tuning, and hardware decisions.
Open development
Public code and shared artifacts make results reproducible and available for independent development.
02 Areas of focus
Local AI on the most capable hardware you can own.
We focus on NVIDIA Blackwell platforms available outside traditional datacenters, with an emphasis on inference performance, efficiency, and usability.
NVIDIA RTX
GeForce RTX 50 Series and RTX PRO Blackwell systems.
DGX Spark
GB10 Grace Blackwell systems for compact local inference.
DGX Station
Workstation-class Blackwell systems for large local workloads.
03 Flagship project
Kernels for the hardware you have.
b12x is an open SM120/SM121 CuTe DSL and Triton kernel library for local LLM inference, targeting DGX Spark and Blackwell-based RTX systems.
Explore b12x on GitHub
b12x / operator map
SM120
$ pip install b12x
04 Join the lab
Contribute.
Run our projects on your hardware, report results, and contribute fixes through the public repositories.