io.net Re-poster

AWS recently raised their prices... again.

These costs keep devs and startups from having a fair chance to succeed.

And we're not okay with that.

That's why while these “hyperscalers” are busy hiking prices, we’re busy opening doors for founders and builders. 🚪✨

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 has just leveled up again.

zai-org/GLM-4.7 is now live.

Features:
•Advanced Agentic Coding & Planning
•Powerful Tool Usage & Web Interaction
•Enhanced Complex Reasoning

Try it now: 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

Năm 2026, và bạn vẫn không biết DePIN là gì hay @ionet làm gì?
Xem cuộc phỏng vấn mới nhất của @jack_ionet với @BitcoinMagazine để cập nhật:
https://www.youtube.com/watch?v=_WJ2rviPV3g

Cơ chế tính toán phi tập trung hoạt động.
Các công ty khởi nghiệp AI & doanh nghiệp đang chuyển sang lựa chọn này thay cho "Đám Mây Lớn".

Nhưng kinh tế của nó đang bị hỏng.

Đó là lý do tại sao http://io.net đang giới thiệu Động Cơ Khuyến Khích Động.

Hãy cùng khám phá cách IDE hoạt động ⤵️
https://io.net/blog/incentive-dynamic-engine