Skip to main contentInstant Clusters — On-Demand Multi-Node AI Compute
FarmGPU offers Instant Clusters — high-performance, multi-node GPU clusters that users can provision in minutes, not months, via a self-serve, on-demand experience in partnership with RunPod. These clusters bring bare-metal performance to cloud-like flexibility, eliminating the traditional barriers of hardware procurement, rack build-out, and operational complexity.
FarmGPU Blog
Key Characteristics
One-Click Multi-Node Deployment
Users can launch powerful multi-node clusters from the RunPod dashboard with a few clicks. Instant Clusters support bring-your-own Docker containers or optimized templates for training, inference, and research workflows.
Pay-Per-Use Economics
Billing is per-second, not per-month, giving teams the flexibility to:
- Run experiments without upfront commitments
- Scale up for training runs and tear down when finished
- Avoid minimum runtime requirements or termination fees
Complete Control
Users retain full control of their cluster lifecycle — start, stop, and reconfigure as needed — without long-term lock-in or opaque pricing structures.
Instant Clusters are built on the same high-performance infrastructure that powers FarmGPU’s bare-metal offerings, including:
400 GB/s between nodes with RDMA Networking Fabric
Clusters leverage an OCP-compliant 800 Gbps backend fabric for GPU-to-GPU communication, delivering low-latency, high-bandwidth interconnects optimized for distributed training and collective operations.
Solidigm PCIe 5.0 NVMe Local Storage
Each node includes eight PCIe 5.0 NVMe SSDs, providing up to 116 GB/s of local storage throughput to ensure that model loading and data pipelines do not bottleneck training runs. FarmGPU Blog
Topology-Aware Communication
Clusters are optimized for high NCCL performance — the communications library that defines training throughput for large models — achieving multi-hundreds-GB/s AllReduce performance across GPU nodes.
Typical Use Cases
Instant Clusters are ideal for teams that need elastic scale with the performance profile of bare-metal systems, including:
- Distributed model training, especially with PyTorch DDP, DeepSpeed, and other frameworks
- Large-scale fine-tuning and experimentation
- High-performance inference workloads
- Burst compute capacity without long-term commitments
This capability gives FarmGPU customers a flexible on-ramp to production-grade AI compute without the overhead of provisioning and managing their own cluster hardware.
Instant Clusters unify the best aspects of cloud and bare metal:
- Cloud-like experience: Self-service deployment, per-second billing, fast iteration
- Bare-metal performance: Optimized interconnects, local NVMe, and hardware-aware tuning
- Integration with your software stack: Works seamlessly with FarmGPU’s control plane, scheduling, and observability tools
This makes them a natural complement to both the on-demand GPU Cloud and managed infrastructure offerings, enabling:
- Rapid experimentation before committing to dedicated clusters
- Burst capacity beyond long-term rentals
- A consistent interface for both transient and persistent compute
