Choose the level of model access, collaboration, compute capacity, and deployment control that fits your research team.
For universities, nonprofit research groups, and investigator-led projects.
For biotech and discovery teams running active antibody or drug-design projects.
For organizations requiring higher capacity, governance, integration, and deployment control.
Plan quotes are based on monthly compute credits, collaborators, and the number of jobs your team needs to run in parallel.
Academic and Core provide limited model access. Enterprise unlocks the complete specialized model library with additional capacity and deployment controls.
Credits reflect the computational work behind predictions, generation, docking, and structure workflows.
Add researchers to one shared project history so decisions, inputs, and outputs stay connected.
Higher concurrency lets teams run more experiments in parallel and shorten iteration cycles.
Add capacity or specialist services when the project demands them.
Increase monthly workload for generation, docking, prediction, and batch analysis.
Ask about creditsAdd researchers while preserving a single project workspace and decision history.
Ask about seatsGive time-sensitive workloads priority access to available compute capacity.
Ask about priorityConnect private data, internal models, and organization-specific discovery processes.
Discuss integrationWe’ll size the plan against your expected models, workloads, users, and data requirements.
Enterprise includes access to all specialized models. Academic and Core provide limited access based on the evaluation period, selected models, compute capacity, and research needs.
Credit use depends on the computational cost of a workflow. Before final public pricing, AI Cloud will define and publish the credit cost for each model and common batch size.
Yes. Academic pricing can be reviewed according to eligibility, expected usage, number of researchers, and whether the work is noncommercial.
Yes. Additional compute credits and team seats are intended to be available as add-ons without forcing a complete plan change.
Private-cloud and on-premise options belong in the Enterprise plan and can be scoped around security, infrastructure, integration, and support requirements.
Tell us which models, workloads, and researchers you expect. We’ll recommend the right credits, concurrency, and deployment level.