High-performance GPU clusters, provisioned in under 60 seconds.
On-demand access to a wide selection of datacenter GPUs. Whether you need a single GPU for rapid prototyping or a 256-GPU cluster for distributed training, CogniCloud Compute provisions exactly what you need — and only charges for what you use.
Provision single or multi-node GPU clusters in seconds. A wide selection of datacenter GPUs with high-bandwidth memory available across all regions.
All nodes ship with full NVLink 4.0 mesh at 3.35 TB/s bidirectional bandwidth. Optimal for tensor-parallel and pipeline-parallel training strategies.
Cut training costs by up to 70% with preemptible Spot instances. Automatic checkpoint-and-resume means interrupted jobs pick up exactly where they left off.
InfiniBand HDR 200 Gb/s interconnects between nodes. Designed for NCCL all-reduce and all-gather operations with minimal overhead.
High-throughput NVMe-backed volumes attach directly to GPU nodes. Read speeds up to 12 GB/s — no more waiting for data to transfer before training starts.
Pre-built containers for PyTorch, JAX, and TensorFlow with optimised CUDA, cuDNN, and NCCL versions. Or bring your own Dockerfile.
| GPU selection | Wide range of datacenter GPUs |
| VRAM per GPU | 80 GB HBM2e |
| GPU per node | Up to 8 |
| NVLink bandwidth | Full NVLink mesh per node |
| Node interconnect | InfiniBand HDR 200 Gb/s |
| Host memory | Up to 2 TB DDR5 per node |
| Local NVMe | Up to 30 TB per node |
| Provisioning time | < 60 seconds |
CogniCloud Compute is currently in development — estimated Q2 2026.
No pricing yet. We offer tailored solutions only.
CogniCloud is in active development. Join the waitlist to get early access and stay updated on our roadmap. No pricing yet — we'll work with each team to find the right fit.
No spam. No pricing pitches. We reach out personally to discuss your use case.