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Seeing a "Not enough available CPU" error on Ocean Network?

It doesn't mean anything is misconfigured. It simply means the environment you selected is at capacity right now.

The fix is simple:

1. Try another node or environment
2. Switch GPU types if your workload allows
3. Or wait a bit. Capacity becomes available as other jobs finish.

https://x.com/oncompute/status/2082859513338888197?s=46&t=sfyIS0XeZHZd-w68hBLkvw
The GPU is no longer the product. Compute is.

No engineer wakes up wanting to rent an H200. They wake up wanting embeddings generated, models fine-tuned, datasets processed, and jobs finished.

The GPU is just the means to get there.

That's exactly what on-demand compute on Ocean Network gives you, with NVIDIA H200s starting at $2.16/hr: https://dashboard.oncompute.ai/

https://x.com/ONcompute/status/2084648803362328621
We're teaching AI agents to write code. The next step is teaching them to provision compute.

ON MCP lets agents discover compute on Ocean Network, choose an environment, and launch jobs using natural language instead of clicking through cloud dashboards.

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

https://x.com/ONcompute/status/2085011695403946247?s=20
Kimi K2 Distilled 14B isn't asking for a GPU cluster. It's asking you to stop overthinking infrastructure.

An NVIDIA H200 has 141GB of HBM3e, enough for LoRA and QLoRA fine-tuning, and you can rent one on Ocean Network from $2.16/hr.

Train your adapter, export it, shut the GPU down, and move on to the next problem.

That's what pay-per-use compute is supposed to feel like: https://dashboard.oncompute.ai/run-job/environments

https://x.com/ONcompute/status/2085386162659594452?s=20
Hey anon, before you reserve GPUs, ask yourself:

1️⃣ Did I size my infrastructure correctly? GPU/CPU, RAM, disk space, and time duration.
2️⃣ Am I paying for resources I'll actually use?
3️⃣ Is my workload close to the compute? Keep your code, containers, and datasets near the compute node to minimize startup time and data movement.

A good reservation starts long before you click "Reserve." Ocean Network helps you get it right from the start.

Get started: https://docs.oncompute.ai/ocean-orchestrator/using-ocean-orchestrator-with-ocean-dashboard

https://x.com/ONcompute/status/2086844269629968741
CEO: "Can we build our own ChatGPT?"

Engineer: "Sure."

Skips the trillion-token pretraining run, reserves an H200 on Ocean Network, fine-tunes Qwen3-8B with LoRA instead.

The smartest engineering decision is usually knowing what not to build

https://x.com/oceanprotocol/status/2087577350007361576?s=20
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 ready👀

Stay close⌛️

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