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Ocean Orchestrator
Run AI jobs from your IDE with a one-click workflow
230 followers
Run AI jobs from your IDE with a one-click workflow
230 followers
Access GPUs worldwide directly from your IDE. Ocean Orchestrator lets you run AI training and inference jobs while paying only for the compute you use. Jobs run on GPUs like NVIDIA H200s across the Ocean Network Escrow-based payments protect both users (data scientists, developers) and node operators, releasing funds only after successful execution, bringing reliable, decentralized GPU compute to real workloads with transparent pricing, global availability, and verifiable job execution at scale




Free Options
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Started experimenting with it yesterday, and I must say I really enjoy working with the workflow
Ocean Orchestrator
Embedding GPU access directly into the IDE where developers already work — Cursor, VS Code, Windsurf — rather than requiring a separate infrastructure dashboard is the right UX decision for making compute feel invisible rather than burdensome. The escrow-based payment system that only releases funds after verified job execution solves the trust problem that plagues most decentralized compute networks; how does Ocean Orchestrator handle job failures mid-execution on a node — does the escrow mechanism cover partial compute costs, or is the user only charged for successfully completed work?
Ocean Protocol
@svyat_dvoretski If a node fails mid-job, you don’t lose funds for unfinished work, and you stay in control of where jobs run.
Ocean Nodes handle failures locally. If a node goes down, the job can restart on the same node once it becomes available again. If you want to run it elsewhere, you can reroute it yourself, as compute resource selection stays fully in the user’s hands.
However, if the failure is caused by the algorithm itself, the job is marked unsuccessful and you’re only billed for the compute time that actually ran, not the full job window. You can read more details about the Ocean Network and Orchestrator in the FAQ here.