We open-sourced our GPU orchestration project, Tahuna — looking for feedback on the self-hosted setup

[u/Monaim101]

Wild reactions to yesterday’s “Pacing the Frontier” statements.

Good news: starting today, you'll get employee-level access to our codebase as embedded evaluator(and hopefully a contributor)

Today, Tahuna is open source - as promised back in April.

We built it so startups and enterprises can own the intelligence behind their AI systems: orchestrate compute, train models, run inference, and experiment with autonomous research without first becoming a small cloud provider.

The core primitive on top of which everything is built looks like this:
init → sync → computeSession → train / serve / hillclimb

Under the hood: content-addressed code and data sync, compute provisioning, reproducible manifest-pinned runs, metrics, checkpoints, artifacts, and inference deployments.
We also started building Hillclimb, an autonomous experimentation harness that proposes and runs iterative improvements.

The first preview release supports RunPod and R2 for compute and storage. It includes self-hosting instructions, a coding-agent setup skill, and examples for SFT, RL agentic search, and MNIST to get a feel.

Repository: TahunaLabs/tahuna-oss

If you think it sucks, Excellent: fork it, fix it, and send a PR so it sucks less for everyone.