Efficiency
Focused on reducing computational, token, latency and energy cost in LLM-based workloads while preserving output quality.

An experimental AI-efficiency project focused on reducing computational, token, latency and energy cost in LLM-based workloads while preserving output quality. This site is the official home for public project information, documentation, results and updates.
RHEA Kernel remains under active private development and experimental validation, focused on reducing computational, token, latency and energy cost in LLM-based workloads while preserving output quality.
Focused on reducing computational, token, latency and energy cost in LLM-based workloads while preserving output quality.
Selected public results and validation material are available in the Results and Documentation sections.
The website tracks public project updates, documentation and milestones over time.
Verified releases, documentation and results are organized into dedicated sections.
Public releases, milestones and announcements.
Public technical and project documentation approved for release.
Published validation material and verified public results.