Ocean Network

Ocean Network Beta is officially ON ⚡️ This is the moment we've been building toward: Run AI workloads on pay-per-use NVIDIA H200s as low as $2.16/GPU hour, straight from your IDE with a one-click code-to-node workflow. Head on to oncompute.ai to claim your $100 complimentary credits in Beta and turn your first job ON! (1/8)

Most AI teams obsess over model quality while ignoring the biggest cost in the stack: compute utilization. An NVIDIA H200 is $2.16 per hour on Ocean Network. The same compute can cost several times more on traditional cloud infrastructure, depending on the provider and availability. One unit of H200 compute is enough to: Fine-tune a model with QLoRA Generate synthetic training data Run large-scale inference Plus, Ocean Network charges you only for what you use, with no vendor lock-in, and payments are made through escrow. Explore available environments: dashboard.oncompute.ai/run-job/enviro…

Somewhere out there, GPUs are folding proteins, training neural nets, and running climate simulations. Yours is collecting dust. Complete the eligibility checks and make your GPU what it deserves to be. Start here: dashboard.oncompute.ai/run-node/setup

@KayKaycandy67 you win, claim your COMPY tokens and get started: docs.oncompute.ai/ocean-network-…

@ONcompute H100s disappeared faster than toilet paper in 2020 😭🔥

The enterprise GPU-buying craze has major "2020 empty supermarket aisles" energy 👀 What got wiped out first? Drop your answer below. $100 in complimentary compute tokens if you get it right.

@xabzxbt you win, claim your COMPY tokens and get started: docs.oncompute.ai/ocean-network-…

@ONcompute Nvidia chips (H100/A100)

@BKoholi7818 you win, claim your COMPY tokens and get started: docs.oncompute.ai/ocean-network-…

@ONcompute First it was GPUs… next thing you know, even cables and cooling systems vanished 😅

@Lilita_CI you win, claim your COMPY tokens and get started: docs.oncompute.ai/ocean-network-…

@ONcompute The first things to disappear were top tier NVIDIA GPUs, lol😄

@Vih_ktoralt you win, claim your COMPY tokens and get started: docs.oncompute.ai/ocean-network-…

@ONcompute NVIDIA H100s (and then the H200s) got wiped out first straight up 2020 toilet paper energy but for AI bros panic buying clusters 😂 Everyone was fighting for allocation like it was the last roll on the shelf.

@NKWADOCHUKWU you win, claim your COMPY tokens and get started: docs.oncompute.ai/ocean-network-…

@ONcompute Definitely toilet paper! It’s the enterprise equivalent of securing that sweet, sweet Nvidia allocation before everyone else panic-buys.

@Christina90986 you win, claim your COMPY tokens and get started: docs.oncompute.ai/ocean-network-…

@ONcompute H100s disappeared faster than toilet paper in 2020 Hope I win

Many compute providers bill by the hour. Your workloads don't run by the hour. With Ocean Network, you pay for execution time and not a cent more, even on the NVIDIA H200. Access some of the most affordable GPUs on the market, configured exactly to what your experiment needs: GPU, CPU, RAM, disk space, and runtime. Run a 22-minute fine-tune and pay for 22 minutes. That's it: dashboard.oncompute.ai

The majority of LoRA, QLoRA, and fine-tuning practitioners are wasting time switching between their IDE and cloud consoles just to provision a GPU. Ocean Orchestrator brings IDE-native GPU compute orchestration into VS Code, Cursor, Antigravity, and Windsurf. Select your exact specs on the Ocean Network Dashboard, including NVIDIA H200 on-demand access at a fraction of hyperscaler rates, and bring that instance into your IDE on a pay-per-use basis. Your logs, outputs, and results land directly in your workspace. You never leave the IDE. Install the Ocean Orchestrator extension and start your next fine-tune in minutes: open-vsx.org/extension/Ocea…

If your AI automations are slowing down as you scale, it's probably not your code. Most teams hit a compute ceiling before they hit a logic one, where inference at scale turns into an infra problem. There's a more efficient way to scale, and it starts at $2.16/hr for an NVIDIA H200 👇

GPU queues are a relic of a world that didn't know better. We fixed it. Fine-tune 70B models, run inference, and process large-scale embeddings on demand on @nvidia H200s through Ocean Network at ~$2.16/hr. The compute you need, the moment you need it: dashboard.oncompute.ai

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: open-vsx.org/extension/Ocea…

Your GPU was always infrastructure. Now there's a second place to point it, one that pays you based on what your hardware can actually do. AI compute is where the next decade of demand is going, and the network for it already exists. Run a node on Ocean Network. Your hardware gets benchmarked weekly across GPU, CPU, and bandwidth, and your score determines your share of a 2,000 $USDC weekly pool. You didn't buy a GPU to sit on the sideline of the biggest infrastructure shift in AI: dashboard.oncompute.ai/run-node/setup

The real moat in AI is compute orchestration. Routing workloads across a peer-to-peer network, coordinating distributed supply, abstracting infra complexity, and turning fragmented compute into a usable execution layer with pay-per-use economics. A layer Ocean Network already built.

Hot take: there's no GPU shortage. There's an allocation problem. Most teams overprovision out of fear and pay for idle capacity. The smarter move is on-demand access, routing to compute only when you actually need it. Start running on demand with Ocean Network: dashboard.oncompute.ai

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: oncompute.ai/blog/ocean-net…

The world doesn't have a GPU shortage. It has an allocation problem. ~90% of GPUs provisioned for AI workloads sit idle or underutilized, yet still bill the organizations that reserved them. You're paying for compute that isn't computing. Turns out, there's a smarter way to do this. Ocean Network gives you direct peer-to-peer access to top-tier NVIDIA GPUs, on demand, for exactly as long as you need them. H200 access from ~$2.5/hr, paying only for what you use: dashboard.oncompute.ai