Solutions · Research labs and AI safety
Run the new weights the week they drop, on hardware the lab controls.
Independent labs and safety teams pick between renting cloud GPUs and eating the price, access and data exposure, or building local and losing weeks to setup. Metrale makes open models run fast on machines researchers own, with a written setup path and results you can reproduce.
Where it fits
Why it fits
- Evaluation, red team and research workloads that must stay private
- A workstation or small cluster instead of a cloud account
- Reproducibility as a requirement, not a preference
- Grant budgets that cannot absorb metered token pricing
Workloads that move first
- Evaluation and red teaming
- Reproducing published results
- Long running research jobs on owned GPUs
How it deploys
The open source engine on owned hardware, with the Enterprise control plane when the lab grows into a cluster. We publish how each setup was configured and what it measured.
The proof we bring
Every number on this site is generated from a record in the repository and comes with a reproduce command. The verification walkthrough shows every step.
Next step
See it against your own workload.
A side by side ladder on your hardware in week one. Your models, your criteria, your receipt.