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A cluster is nodes identical machines of gpusPerNode GPUs each, placed in one location on a private high-bandwidth interconnect, and managed as a single resource: one quote, one launch, one price, one terminate. Use it when a model does not fit one machine (DeepSeek-V3 or Kimi-K2 class) or for distributed training. The normalized contract guarantees private node connectivity, not a specific fabric such as InfiniBand, RDMA, or NVLink. It does not expose enough provider identity to verify one after placement. If a fabric is a hard requirement, deploy through the provider passthrough from the outset and verify it there.

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What every node gets

Set MALLOC_ARENA_MAX=1 in env for tensor-parallel workloads. The provider-agnostic cluster contract does not currently expose /dev/shm sizing; workloads that require a larger shared-memory mount need a provider-native deployment path.

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Shapes

Self-serve clusters are 2 to 8 nodes of 1 to 8 GPUs each (16 to 64 GPUs at full width). Larger clusters are arranged through sales. gpusPerNode cannot exceed what the accelerator offers per machine. orchestrator picks the topology:

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Quote, then launch

1

Quote the shape

The quote prices the whole cluster: every node’s GPUs, every root disk, and the shared volume. Inter-node networking is included in the rate. availability is the stock signal for one node of this shape; whether every node can be placed together is confirmed only at launch.
2

Launch from the quote

Workload settings (env, ports, SSH keys, dockerStartCmd) can be added at launch without changing the price. Repeating a priced field with a different value answers 409 price_changed.
3

Connect

connections lists the primary node’s SSH, every node’s SSH and its address on the interconnect. Logs stream per node; rank 0 by default.
Direct REST:

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Storage

A cluster mounts at most one persistent volume, shared by every node at the same path. Create it with the cluster (storage) so it lands in the cluster’s location, or mount an existing one (volumeId), which pins placement to where that volume lives. The volume survives terminate and bills until you delete it; you cannot delete or grow it while a cluster is attached. Weights for a 600 GB to 1 TB model take 35 to 70 minutes to download at typical rates. Put them on the shared volume once and relaunch against it.

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Lifecycle

running is infrastructure readiness. It does not probe a model server, distributed rendezvous, or application health endpoint. Make the shared command rank-aware and run your own readiness check before admitting traffic. There is no stop. A cluster bills from readyAt until you terminate it:
Terminate is always accepted, even mid-provision. If payment grace expires on an unpaid hour, the cluster is terminated (not stopped); the shared volume is kept.

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Recover a degraded cluster

A cluster that loses a node after it was admitted goes degraded and keeps billing at the locked rate until you act. By default AI Reserve leaves it for you. Opt into automatic recovery per cluster:
On the next health pass every node that is not running is brought back one by one through the provider’s own restart or start, on the same hardware, with the same interconnect address. Healthy nodes, the shared volume and the rate are untouched, so a distributed job that tolerates a node restart can resume without a relaunch. Attempts are bounded per unhealthy episode exactly as for instances, the recovery object on the cluster reports the episode, and nodes[].status shows each member. Make one attempt now with:
A node the provider cannot bring back is skipped and the attempt resolves on the remaining nodes; once every attempt is spent the cluster stays degraded with lastError: recovery_exhausted and terminate is the way out.

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Pricing

Per-GPU pricing uses the provider’s cluster rate, which differs from the single-machine rate for the same accelerator. The whole cluster accrues hourly while any node runs, at the rate locked in the quote.

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