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Just "spin up a GPU" is not a strategy.

Before the workload starts, configure the exact compute you need on Ocean Network: GPU, CPU, RAM, disk, and runtime.

Then bring that environment straight into your IDE with Ocean Orchestrator.

H200s are live at $2.16/hr: https://dashboard.oncompute.ai/run-job/environments

https://x.com/oncompute/status/2088265384331976997?s=46&t=sfyIS0XeZHZd-w68hBLkvw
Barry looks tired

Something's been running behind the scenes for a while now, and it's almost readyπŸ‘€

Stay closeβŒ›οΈ

https://x.com/ONcompute/status/2089390296379392010?s=20
Reserving an H200 is as easy as ordering a coffee, and at $2.16/hr, it's cheaper too.

Connect the Ocean Network MCP server to your agent and provision GPU compute for your AI training workloads with a single prompt.

Get started here: https://docs.oncompute.ai/on-mcp/quickstart

https://x.com/ONcompute/status/2090014411083653218?s=20
Ask Claude to "find compute to fine-tune this model on my dataset using Ocean MCP" and it handles the busywork.

It finds available GPUs on Ocean Network, shows you rates so you can pick, runs the job, and hands you the finished model.

Try it for free: https://docs.oncompute.ai/on-mcp/quickstart

https://x.com/oncompute/status/2092327921427919100?s=46&t=sfyIS0XeZHZd-w68hBLkvw
Ask Claude to "find compute to fine-tune this model on my dataset using Ocean MCP" and it handles the busywork.

It finds available GPUs on Ocean Network, shows you rates so you can pick, runs the job, and hands you the finished model.

Try it for free: https://docs.oncompute.ai/on-mcp/quickstart

https://x.com/oncompute/status/2092327921427919100?s=46&t=sfyIS0XeZHZd-w68hBLkvw