Cloud GPU hours are valuable for large-scale jobs like AI training, yes. But for chemistry calculations – running AI predictions, performing QC processing – the economics shift dramatically: We need machines with 2-4 cores, 32 GB RAM, and 1 TB disk space, which cost €72–€216 per month in the cloud. But owning a local machine costs a fraction of that.
Example: A desktop, $50, from eBay with 32 GB RAM and a 1 TB SSD (Fujitsu P970) effectively becomes a near-free local server for most computational chemistry workloads. Paramus leverages this efficiency. Just install the BRAIN Server. And perform 24/7 calculations.
Most students and laboratories already own under-used hardware: older Core-i5 desktops, lightweight office PCs, and laptops with around 16–24 GB RAM. Paramus transforms this aging equipment into a functional chemistry engine capable of running kinetics models, descriptor pipelines, polymer analytics, and everyday ML inference. Refurbish, Win11 them and this hardware becomes a stable prediction node for routine scientific work, incl. LAMMPS, psi4 etc on Docker.
Paramus is an Operating System for Chemistry
With the BRAIN Server:
- AI and physics models operate fully offline
- Data stays on the local drive, with no up/down I/O
- Agents, tools, and models scale “only when needed”
- Higher modes like cluster, cloud, and container build on the same core
This design ensures that chemistry remains fast, private, and precise, regardless of laboratory budget or infrastructure. Paramus makes chemistry AI accessible everywhere. No massive servers. No vendor lock-in. Just real performance on the machines scientists already own. This is why Paramus.ai bets on local installation.