OceanProtocol News

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

Finding an available H200 at a fair price, without waiting in a queue, is still the hard part Ocean Network gives you access to idle H200 capacity across providers, so you can launch the GPU that fits your workload and only pay while it runs From $2.16/hr: https://dashboard.oncompute.ai/run-job/environments https://x.com/oncompute/status/2082481774362538140?s=46&t=sfyIS0XeZHZd-w68hBLkvw

Here's the proofread version: "I want to fine-tune Llama 3 8B on my dataset. Find me an H200 node and get it running using Ocean MCP." One prompt, and Ocean MCP finds you a live node with real specs and pricing, no external search required. Then it walks you through the rest: dataset, fine-tuning approach, and funding, before anything spends. Get started here: https://docs.oncompute.ai/on-mcp/quickstart https://x.com/oncompute/status/2082120644700016682?s=46&t=sfyIS0XeZHZd-w68hBLkvw

The hardest part of using an H200 isn't the H200. It's everything that happens before your code ever runs, and Ocean Network skips most of that. Launch an NVIDIA H200 in minutes for $2.16/hr on the Ocean Network Dashboard: https://dashboard.oncompute.ai/run-job/environments https://x.com/oncompute/status/2081756500909805965?s=46&t=sfyIS0XeZHZd-w68hBLkvw

The team at @ONcompute asking the question many have been avoiding: Why own an H200 when you only need it for 37 minutes? Rent the compute. Ship the model https://x.com/oceanprotocol/status/2080962042312249407?s=46&t=sfyIS0XeZHZd-w68hBLkvw

What if your AI agent could find a GPU, compare prices, and launch the job itself, without you opening a dashboard or writing a custom integration? That's now possible with Ocean MCP⬇️ https://x.com/oceanprotocol/status/2080649198761079119?s=46&t=sfyIS0XeZHZd-w68hBLkvw

Distilling GLM 5.2 is basically a five-step workflow now You don't need a research lab or weeks of infrastructure setup anymore. 1) Grab the open, MIT-licensed GLM 5.2 weights: https://docs.z.ai/guides/llm/glm-5.2 2) Write your distillation script and package it as a Docker image 3) Open Ocean Network Dashboard and choose an H200: https://dashboard.oncompute.ai/run-job/environments 4) Attach your dataset, hit run from VS Code, Cursor, or Windsurf with Ocean Orchestrator and watch the logs stream live: https://open-vsx.org/extension/OceanProtocol/ocean-protocol-vscode-extension 5) Download the distilled model straight back into your project folder The interesting part is how little infrastructure you have to think about to get it done https://x.com/oceanprotocol/status/2080558350253851036?s=20

Want to join us at Pragma Lisbon? We've got 5 tickets to give away😄 Meet the Ocean team & learn how to run training jobs on Ocean Network on @nvidia H200s while paying only what you use Code expires tomorrow Claim yours with PRAGMAOCEAN: https://luma.com/pragma-lisbon2026 https://x.com/oncompute/status/2080294109059678719?s=46&t=sfyIS0XeZHZd-w68hBLkvw

An Uber across town costs more per hour than an NVIDIA H200 on Ocean Network. $2.16/hr gets you 141GB of HBM3e memory and 4.8TB/s of bandwidth, enough headroom to run 70B class models on a single GPU, with room left over for KV cache that most cards can't spare. Access here: https://x.com/oncompute/status/2079951350457385295?s=46&t=sfyIS0XeZHZd-w68hBLkvw

MCP is becoming the interface layer for agentic AI. Once an agent has an MCP endpoint, it doesn't need provider-specific APIs. It just discovers compute, checks live pricing, runs the job, and retrieves the results. That's what agent-native infrastructure looks like https://x.com/oceanprotocol/status/2079602362814001331?s=20

The clock hit 90, and the match didn't care. Spain kept creating chances after regulation ran out, and it took until the 106th minute, deep into extra time, to find the goal that actually settled it. An AI batch job doesn't know what an hour is either; it stops when the job's actually done, not when the clock hits a round number. Ocean doesn't round up, and you get billed for the seconds the GPU actually worked, not the hour it happened to fall in. Access on-demand compute: https://dashboard.oncompute.ai/run-job/environments https://x.com/ONcompute/status/2079227333161152829?s=20

Every World Cup cycle, the tournament gets bigger; this year's 48-team format nearly doubled the total matches from 2022 Compute scales the same way: more data, more parameters, more memory needed to hold it all. That's exactly what H200's 141GB of HBM3e is built for Run your next job from $2.16/hr: https://dashboard.oncompute.ai/run-job/environments https://x.com/ONcompute/status/2078126576638763238?s=20

The Singapore Court of Appeal has affirmed the Singapore High Court’s decision that confidentiality has been lost in relation to the emergency arbitration proceedings. The Court of Appeal upheld the High Court’s finding that having regard in large part to Fetch’s conduct, Fetch could not have reasonably believed that confidentiality continued to subsist. Following this decision, the interim orders preserving confidentiality pending the appeal have been discharged. Therefore, we republish the emergency arbitrator’s award here: https://x.com/oceanprotocol/status/2078017924061638907?s=46&t=sfyIS0XeZHZd-w68hBLkvw

Your AI agent can now run compute jobs on Ocean Network🤖 🔌Connect Claude, Cursor, ChatGPT, GitHub Copilot & more at our hosted MCP endpoint: mcp.oncompute.ai/mcp It can discover compute providers, write algorithms, launch jobs & manage storage using natural language https://x.com/oncompute/status/2077670789835293154

Need one H200 for just 20 minutes? That's what you pay for Most compute contracts make you pay for the biggest GPU config upfront, whether your job needs it for 10 minutes or 10 hours. Ocean Network lets you configure GPU/CPU type, RAM, Disk space, & time duration to run compute workloads on a pay-per-use basis Configure your exact job: https://dashboard.oncompute.ai/run-job/environments https://x.com/oncompute/status/2077431748234023383?s=46&t=sfyIS0XeZHZd-w68hBLkvw

Ideas are easy; shipping is what counts Build on NVIDIA H200s at $2.16/hr, launch your workload, and let the results speak for themselves. Claim 100 complimentary tokens and run your first job on Ocean Network: https://docs.oncompute.ai/ocean-network-dashboard/claim-your-compy-tokens https://x.com/oncompute/status/2077076155396714854?s=46&t=sfyIS0XeZHZd-w68hBLkvw

Full fine-tuning isn't the only way to adapt Llama 70B LoRA can achieve performance close to full fine-tuning while using a fraction of the GPU memory. QLoRA reduces memory requirements further, making some Llama 70B fine-tuning workloads feasible on a single high-memory GPU Ocean Network lets you choose the setup that fits your workload and pay only for the compute you actually use: https://dashboard.oncompute.ai/run-job/environments https://x.com/oncompute/status/2076705715184640141?s=46&t=sfyIS0XeZHZd-w68hBLkvw

We’re bringing @ONcompute to Pragma Lisbon 2026! 🇵🇹 Come find us at the booth and see how easy it is to access on-demand compute for your next AI project. We’ll tell you all about it over a couple of pastéis https://x.com/oceanprotocol/status/2075574807316287873?s=46&t=sfyIS0XeZHZd-w68hBLkvw

The best fleets aren't owned. They're joined Every GPU on Ocean Network belongs to someone who decided to put it to use, instead of letting it sit idle Every node gets benchmarked, stress-tested, proven, before it touches your job That's what makes our fleet efficient Choose your node here: https://x.com/oceanprotocol/status/2074939163388895546?s=46&t=sfyIS0XeZHZd-w68hBLkvw

You don't pay for compute on Ocean Network. You pay for verified completion of compute✅ Book an H200 for $2.16/hr and your budget is locked in escrow before the job starts Once the network verifies completion, only your exact runtime cost is released and the remaining funds are automatically refunded 😎 Try it: https://dashboard.oncompute.ai/run-job/environments