Model training at frontier scale.
From a single node to 8,000-GPU fabrics. Lumengrid combines bare-metal accelerators, full-mesh RDMA networking, and fault-tolerant tooling so your largest training runs are the most boring part of your week.
Built for runs that last weeks.
Elastic checkpoints
Streaming, incremental checkpoints with restart-from-any-shard recovery. Lose a node, not an epoch.
Fault-tolerant jobs
Dead-node detection, automatic rescheduling, and topology repair keep a 1,000-GPU run moving.
Full-mesh fabrics
Up to 1.2 TB/s per GPU between nodes — the bandwidth tensor parallelism actually needs.
Job-level telemetry
Step time, MFU, and hardware health correlated per job, from day one of the run.
Cost guardrails
Budgets, auto-stop, and idle detection so a hung job never silently burns capacity.
Experts on call
Distributed-training engineers who have debugged allreduce at 3 a.m., so you don't have to.
From lab run to frontier run.
| Scale | Hardware | Typical stack |
|---|---|---|
| Prototype | 1× H100 node | Single-node FSDP or DDP |
| Lab | 4–16 nodes of H200 | FSDP over NVLink, elastic checkpoints |
| Production | 50–250 nodes of B200 | 3D parallelism, tensor + pipeline + data |
| Frontier | 1,000+ nodes of B200 | Custom scheduling, kernel tuning, dedicated pod |
Ready to push the frontier?
Provision bare-metal GPUs in minutes, scale capacity on demand, and get a real engineer on call — not a ticket queue.