Solutions
Train at one-third the cost.
Bare-metal GPU clusters with 3.2 Tbps RDMA fabrics, dedicated to your job for the duration of the run. Same hardware everyone else trains on — at one-third the price, available the same day.
Performance envelope
What we deliver on training jobs.
What's included
Everything a training job needs.
Bare metal, single tenant
Dedicated NVIDIA, AMD, or Intel hardware for the duration of the reservation. Nothing else runs on the box.
3.2 Tbps RDMA
InfiniBand NDR or 800 GbE RoCE. Non-blocking topology, predictable bandwidth, low tail latency.
High-throughput storage
Lustre and WekaFS pools sized to feed B200-class data parallelism. Snapshots between nodes are inexpensive.
Live observability
Per-step throughput, comm/comp split, gradient norms, kernel timing — streamed to your TensorBoard or a hosted dashboard.
Vendor-neutral runtime
The same training script runs on NVIDIA, AMD, and Intel. Port at the SKU layer, not the source layer.
Checkpoint and resume
Atomic checkpoints to object storage, resume across nodes, seamless across hardware failures. Full job state, not just weights.
Training shapes
What we run for customers.
Pre-training
Foundation-model pre-training from scratch. 1024-4096 GPU clusters, multi-week runs, dedicated SREs paired to your job.
Continued pre-training
Domain adaptation on top of an open-weight base. Smaller cluster, shorter jobs, predictable cost; we have run this for legal, biomedical, and code.
Fine-tuning
LoRA, full fine-tune, RLHF. 8-128 GPUs typically. Same node-level performance as pre-training, packaged for shorter timelines.
FAQ
Training questions.#
Get a training quote.
Tell us the cluster size, the model size, the duration. We respond with a written quote within five business days.