io.net Re-poster

AI builders currently have very few options for GPU compute, and they’re all Big Cloud providers.

And if you want to avoid the costs of buying GPUs for your model, what do you do?

The answer is DePIN.

Always-on AI agents don’t run on waitlists.
They run on scalable GPU infrastructure.

Here’s why it matters 👇
https://startupnews.fyi/2026/02/04/always-on-ai-agents-gpu-infrastructure/

Up to 60% of an AI startup's budget goes to infrastructure costs.

Not engineering. Not product development. Not sales or marketing. Infrastructure.

But there's another way.

Decentralized compute can cut costs by 70%. That can be the difference between bringing a killer product to market and turning off the lights.

Up to 60% of an AI startup's budget goes to infrastructure costs.

Not engineering. Not product development. Not sales or marketing. Infrastructure.

But there's another way.

Decentralized compute can cut costs by 70%. That can be the difference between bringing a killer product to market and turning off the lights.

Utility.

It's that simple. That's what's driving real growth in DePIN.

That's why we rebuilt our tokenomics model to be demand driven and utility focused.

If you haven't read the litepaper, now's your chance. If you haven't shared your thoughts, we want to hear from you. The community feedback period ends Feb 27.

AI’s hidden cost isn’t models, it’s compute.

@Gaurav_ionet breaks down why fintechs underestimate how quickly centralized cloud economics erode AI ROI, and why success with users doesn’t always translate to success on the balance sheet.

Read the full article⤵️

If you’re building an AI model, you probably need a quick cheat sheet with some GPU performance numbers for top GPUs.

We’ve got you covered...

What will you build using IO Cloud?

18 new AI agents just dropped on IO Intelligence

🛠 Dev tools (GitHub, Jira, Linear, ClickUp)
🌐 Research (Web, YouTube, News)
📊 Finance (Crypto and Stocks)
🧠 Language (Summarize, Translate, Moderate, Classify)
💬 Comms (Slack)

One Platform. Open Source. Affordable Compute.

Explore ⤵️

There actually is a chasm of difference between renting random GPUs and running an actual cluster:

🔗 Unified memory access across nodes
⚡ Low-latency interconnects (not public internet)
🎯 Orchestration that doesn't bottleneck at coordination

You're NOT training models faster because you have more GPUs. You're training faster because the GPUs can actually talk to each other without waiting.

Check out our complete breakdown of GPU clusters for beginners:

GPU data centers cost $200K+/month just to cool and use 15-30 MW of power. Big Tech marks this up 10x and calls it "enterprise pricing."

Decentralized compute cuts costs 90% by removing the middleman.

Full deep dive: https://io.net/blog/gpu-data-centers

You’re an AI startup trying to decide between Cloud or On-Premises GPU.

Here’s the cost and ROI breakdown you need. 🧵

GLM-4.7 built by @Zai_org just dropped on io.intelligence

LiveCodeBench: 84.9%
Claude Sonnet 4.5: 64%

Open source model outscoring Anthropic's flagship on coding benchmarks. The "Preserved Thinking" mechanism actually works for long agentic sessions.

Read more:

.@jack_ionet explains how @ionet is redefining GPU access with a decentralized, demand-driven marketplace in an interview at @SolanaConf.

By leveraging @solana and the Incentive Dynamic Engine (IDE), https://t.co/ZuybGWvRkH is making high-performance compute more affordable, transparent, and sustainable, specially for AI builders.

This is Web3 solving a real problem.

Watch the full interview:

IO Intelligence снова повысил свой уровень.

zai-org/GLM-4.7 теперь доступен.

Функции:
• Расширенное агентное программирование и планирование
• Мощное использование инструментов и взаимодействие с вебом
• Улучшенное сложное рассуждение

Попробуйте сейчас: https://ai.io.net/ai/models

CaaS v2 is live with predefined container recipes, removing the guesswork around which container to run and how to configure it.

If you’re running GPU workloads, it’s worth checking out ⤵️

@ionet 2025 wrapped:

✋ Five case studies with receipts
🤝 21 partnerships
👆 1 tokenomics redesign that reinvents DePIN economics

The teams paying hyperscaler rates didn't make it into this list:

https://io.net/blog/2025-io-net-year-in-review

2026 год, и вы все еще не знаете, что такое DePIN или чем занимается @ionet?
Посмотрите последнее интервью @jack_ionet с @BitcoinMagazine, чтобы быть в курсе:
https://www.youtube.com/watch?v=_WJ2rviPV3g

Decentralized compute works.
AI startups & enterprises are turning to this alternative to “Big Cloud”.

But its economics are broken.

That’s why http://io.net is introducing the Incentive Dynamic Engine.

Let’s explore how IDE works ⤵️
https://io.net/blog/incentive-dynamic-engine

Корпоративный ИИ не должен быть связан с ценами на инфраструктуру для предприятий.

IO Inteligence позволяет стартапам в области ИИ и уже существующим бизнесам интегрировать модели в существующие рабочие процессы, чтобы получить все необходимое без больших первоначальных затрат или сложности. ⤵️