Ocean Protocol

Meet Ocean: Tokenized AI & Data.

Ocean Network BETA is ON: @ONcompute

[Ocean Protocol @oceanprotocol]

https://t.co/3Lwl1TK71c

[Ocean Protocol @oceanprotocol]

You bought a monster GPU dreaming of the next AAA title. The next AAA title isn't out yet.

Put it to work while you wait. Run an Ocean node.

Ocean Network is a peer-to-peer compute network. Once your node joins the pool and becomes an Ocean node, anyone whose specs match your hardware can rent it to run their AI workload, and you get paid for it.

Give your GPU a job: https://t.co/E2dAMlUqFA

[Ocean Protocol @oceanprotocol]

You don't need a reservation for innovation. You need compute when the idea arrives.

Ocean Network provides on-demand NVIDIA H200 access from $2.16/hr, so you can run inference, fine-tune models, and test AI workloads without waiting for capacity to free up.

To help you get started and experiment in peace, we're offering $100 in complimentary tokens.

Claim your tokens: https://t.co/fv9xxluSzb

[Ocean Protocol @oceanprotocol]

NVIDIA H200s are becoming one of the best GPUs for multi-agent AI workloads.

Agent systems create massive KV cache pressure, parallel reasoning demand, and long-context memory strain across multiple active inference streams.

That's exactly where H200s shine, with 141GB HBM3e memory and massive memory bandwidth built for high-concurrency AI workloads.

Access them through the Ocean Network Dashboard from just $2.16/hr on a pay-per-use basis: https://t.co/leBQPfNnnd

[Ocean Protocol @oceanprotocol]

Full fine-tuning a 24B model on a single GPU wasn't possible a year ago. Now it's a decentralized compute conversation: spin up an H200 on Ocean Network, fine-tune, pay for what you use, and shut it down.

The moat isn't the model anymore. It's what you fine-tune it on 🖥️

[Ocean Network @ONcompute]

Quiet tip: a single H200 can make full fine-tuning of Mistral Small 24B practical.

Most teams never discover this because they rarely get access to that class of hardware. Ocean Network gives developers on-demand access to NVIDIA H200 GPUs on a pay-per-use basis.

What does that unlock?
For workloads where full-parameter training makes sense, you can train the model itself on your domain knowledge. Fine-tune on internal documentation, support conversations, function-calling workflows, and industry-specific datasets.

The H200's 141GB of HBM3e memory enables training configurations that are difficult or impossible on smaller accelerators.

The result is a model that understands your product, your terminology, and your workflows.

Access H200 compute from $2.16/hr on Ocean Network: https://t.co/ge9uwnrBQ6

[Ocean Protocol @oceanprotocol]

Free $100 in complimentary GPU tokens, so you can build and experiment first, in peace.

Claim them on the Ocean Network (@ONcompute) dashboard and spend them on GPUs across a peer-to-peer compute network.
Two minutes to claim, and tokens land straight in your wallet:
https://t.co/fv9xxlukJD

[Ocean Protocol @oceanprotocol]

Here is the cheapest way to run Llama 4 in 2026:
Pick your GPU on Ocean Network (@ONcompute), pay only for execution time with payment secured in escrow, and take that setup straight into your IDE through Ocean Orchestrator.

Start here: https://t.co/JEtKeeVz1c

[Ocean Protocol @oceanprotocol]

If you're building multi-agent systems, you've probably already noticed how fast orchestration overhead compounds. KV cache grows, inference concurrency spikes, and suddenly GPU memory and bandwidth become a problem.

Why does that happen? Running planner, retrieval, memory, and reasoning agents in parallel puts real pressure on infrastructure. This is where multi-agent orchestration becomes a serious compute workload. One slowdown in throughput and the entire pipeline slows down.

The NVIDIA H200 Tensor Core GPU was built for workloads like this. 141GB HBM3e VRAM and massive memory bandwidth, designed for long-context, memory-intensive AI systems operating at scale.

The best part? H200 GPUs are available on demand at $2.16/hr on Ocean Network: https://t.co/EspCMRlOmR

[Ocean Protocol @oceanprotocol]

The most transformative tech of the decade is being built on the most broken infrastructure model imaginable, with 3 core problems:

1. Enterprises overprovisioned GPUs during the AI boom, and ~95% of that compute now sits idle.
2. Developers on the other side can't get on-demand GPU access for weeks.
3. And if you reserved a cluster you're not fully using, you're billing for idle silicon that isn't doing anything.

Ocean Network (@ONcompute) built a coordinated global on-demand compute layer, not a single vendor's inventory with a waitlist stapled to it.

Developers browse available compute by specs, GPU type, RAM, and duration, and pay only for what they actually use. Node operators on the other side earn on hardware that would otherwise sit dark.

That includes NVIDIA H200s starting at ~$2.16/hr: https://t.co/EspCMRlgxj

[Ocean Protocol @oceanprotocol]

With the advent of Ocean Network (@ONcompute), the distance between idea and execution is narrowing.

Being able to provision global GPU resources on demand from a unified dashboard changes the speed of iteration.

More iteration cycles, more robust AI systems.

[Ocean Network @ONcompute]

Embeddings at scale are mostly a solved problem. Waiting around for GPU infrastructure setup so you can run them is not.

You're generating embeddings on a 50k-document dataset. Locally, it ties up your machine for hours. A cloud instance adds another 30 minutes of setup before the job even starts.

With the Ocean Orchestrator extension, you pick a compute environment from the Ocean Network Dashboard, bring it into your editor, write the script, and hit Start Compute Job. Logs stream into your Output console as it runs. When it finishes, outputs land in your local results folder.

Install the extension and run containerized pay-per-use compute jobs: https://t.co/VaH6G1UBru

[Ocean Protocol @oceanprotocol]

An NVIDIA H200 has 141GB of HBM3e memory and rents for roughly $2.16/hr on Ocean Network (@ONcompute), with jobs running up to 12 hours.

In that time, a small team can run a serious LoRA/QLoRA fine-tune of Llama 3.1 70B on proprietary data, experiment with different training configs, and end the day with a domain-adapted model tuned for their exact workflow.

On narrowly defined internal tasks, these models can outperform frontier general-purpose LLMs.

Many startups spend thousands per month locking themselves into reserved GPU cloud contracts just to access this kind of capability.

On the Ocean Network Dashboard, you spin up an H200 node, run the job, and pay only for the compute you use: https://t.co/leBQPfNnnd

[Ocean Protocol @oceanprotocol]

What if running a GPU job felt like running a local script?
Here's how it actually works:

1. Pick your compute environment inside the Ocean Network Dashboard, browsing live benchmarked nodes by GPU/CPU, RAM, disk, and duration.
2. Fund the job in $USDC through escrow-secured payments, so you're only charged for the compute you actually use.
3. Take that exact setup into your IDE via Ocean Orchestrator, where your code runs on remote GPUs while logs stream live and results come back directly to you.

Get started with NVIDIA H200s on pay-per-use pricing from as low as $2.5/hr: https://t.co/leBQPfNVcL

[Ocean Protocol @oceanprotocol]

The network is live. The nodes are benchmarked. The ambassador program is open. Good time to get involved.

[Ocean Network @ONcompute]

We're opening a few spots for Ocean Network ambassadors. Step in and help shape how the world accesses compute.

1. What you'll do: Take something complex and make it click. Break down how Ocean Network turns compute into a commodity and peer-to-peer verifiable computation into a global market. Use your format: videos, tutorials, infographics, X carousels. Show up where real conversations are happening.

2. How it works: You apply, we review, you get into a private Discord, pick your first task, and you're in. From there, it runs in monthly cycles: you create, submit, and keep building.

3. Rewards: Your work earns points based on quality, reach, and engagement. The better your content performs, the bigger your share, with bonuses for top contributors.

All the details here:
https://t.co/723sL7h5Fh

[Ocean Protocol @oceanprotocol]

Here's everything you need to get started 👇

Full campaign details: https://t.co/rrvmpFNFtR

Join the campaign: https://t.co/8nRlCXysUS

[Ocean Protocol @oceanprotocol]

Ocean Network Zealy Season 2 is HERE 🎉

Learn, spread the word, and show the world how Ocean Network coordinates globalized idle GPU compute for AI developers.

Top 100 participants split a $2,000 $USDC pool 💰

Deadline: June 5

Ready to climb the leaderboard? Details below 👇

[Ocean Protocol @oceanprotocol]

A long time ago in a data center far, far away… someone was paying for idle GPUs.
Not anymore.
May the 4th be with you. 🌊

[Ocean Network @ONcompute]

May the 4th be with your GPU workloads.

A distributed fleet of Nvidia H200s, coordinated across the globe and ready to run your AI jobs on demand, with pay-per-use billing and escrow-secured payments.

The Force has an address: https://t.co/wB2LGQkI4r

[Ocean Protocol @oceanprotocol]

Ocean Network (@ONcompute) is a decentralized compute network where everyone wins.

Users define the resources, pay for what they consume, and the moment the job is done, the billing stops, all secured through escrow-backed payments.

Developers can launch containerized jobs directly from their IDE: every execution isolated, every run reproducible, with signed attestations and on-chain provenance built in.

GPU owners can monetize their hardware by joining the network and earning from real compute jobs routed their way.

And the cherry on top?

Strictly benchmarked NVIDIA GPUs for under $3/hr: https://t.co/ojpbUGegrt

[Ocean Protocol @oceanprotocol]

Compute on Ocean Network is benchmarked, verified, and open for jobs 🖥️

The best part? GPU owners earn from every node that makes it through.

2,000 $USDC is distributed weekly to node runners whose hardware passes strict benchmarks.

Put your GPU to work, start TODAY: https://t.co/nHUqjD0Gkg

[Ocean Network @ONcompute]

Fresh compute nodes are live on Ocean Network 🥞

Last week, we launched the Incentives Program, and GPU owners have been putting their compute to work ever since.

Every node has been strictly benchmarked to handle heavy workloads, full scores and history are right there on the dashboard.

Pick your node, filter by GPU, CPU, RAM, disk, and duration. Submit your job and pay only for what you use, locked in through escrow-secured payments.

Stop sitting on your project.
Verified compute is ready when you are: https://t.co/ge9uwnrBQ6

[Ocean Protocol @oceanprotocol]

Your GPU just got a job offer in Ocean Network 🎉

Every AI training run and inference job needs reliable compute behind it, and now there's a 2,000 USDC weekly pool rewarding the GPU owners actually showing up to provide it 👇

[Ocean Network @ONcompute]

Ocean Network Incentives are live 🥳

GPU owners, this one's for you, and oh, it's good 👀

We're putting 2,000 $USDC into the weekly reward pool for nodes laying the foundation of our peer-to-peer compute network for AI & ML developers globally.

It's time to put your GPU to work🧵
(1/9)

[Ocean Protocol @oceanprotocol]

At this point, renting an H200 on Ocean Network is cheaper than your coffee.

GPUs on demand — GTX 1060s, Tesla T4s, H200s — all under $3/hr on execution-based billing.

See for yourself: https://t.co/x1PYVmzhsB

[Ocean Protocol @oceanprotocol]

The gap between "I have a model to train" and "my job is running on an H200" should not be measured in days.

Ocean Network runs on pay-per-use pricing with escrow-secured payments, and three features make it genuinely hard to go back to anything else:

1. Test your exact workload on real compute before spending anything
2. Take your compute environment inside your IDE via Ocean Orchestrator
3. Spin up the best GPUs on the market with no waitlists

Get started: https://t.co/MkE92NvZ1G