io.net Re-poster

Amazon, @Google and @Meta burned $45 billion in cash last quarter.

A year ago, they generated $36 billion.

Owning AI infrastructure is getting expensive.

Accessing it doesn’t have to be. @ionet
https://tinyurl.com/3mxsrm8b

You came to rent a GPU.

You ended up funding the whole cloud.

Infrastructure overhead. Managed service premiums. Fees to move your own data.

Every extra dollar is budget you can’t spend building.

Rent the GPU and skip the rest with @ionet.

https://io.net/blog/why-does-gpu-cloud-cost-so-much-the-real-economics-behind-aws-azure-and-gcp-pricing

AI is about to compete with everyone for compute.

Jack Collier, our Chief Growth Officer, is at Hong Kong FinTech Week on Nov 3 to talk about what that means for finance, builders and infrastructure.

“When AI Sweeps Over the Infrastructure”
1:35 pm - Hall 5FG

The AI build-out needs $2.6T a year by 2030.

That’s according to @BCG.

But there are two big conditions. The chips need to stay busy, and the older ones need to keep earning.

Idle hardware is the enemy.

Good thing that’s what we’re working on at https://io.net.

Short-term GPU contracts can cost nearly 2x long-term deals.

It's the same chips, and the same data centers. But with a vendor’s term-pricing ladder.

@ionet works differently.

One network of providers, priced by real-time supply and demand. No contract tiers to choose between.

You shouldn’t have to pick between flexibility and a fair price.

Helium moved. Render moved. Akash is voting on it, 98% yes with the vote still open.

Different networks, same conclusion. Build the product, not the chain.

@solana is where DePIN goes to scale.

We’ve been here since day one.

Microsoft is offering buyouts to up to 60,000 staff.

Microsoft is also spending $175 billion on AI this year.

That’s what consolidated AI looks like. A few giants hold the compute, capital, and control.

We're building the other version.

AI for the many, not the few.

Most GPU contracts assume you can predict the next 12 months.

You can’t. Nobody can.

@ionet gives you on-demand capacity for everything above your baseline, so you stop paying for GPUs you aren’t using.

The framework for deciding how much to commit, and how much to keep flexible, is in the blog.

$29 million in total network earnings.

Big cloud is borrowing to build.

We’re growing on real usage.

$40 billion of debt to buy GPUs.

It comes with a warning from @elonmusk. Lenders have almost entirely shut the door on anyone whose business depends on data centres.

Borrow, build, and hope demand arrives before the interest does. That model is starting to break.

But there’s another way.

Aggregate capacity that already exists, put it to work, and scale with demand instead of with debt.

That’s @ionet.

Getting GPUs is half the battle.

The other half is making the economics work.

Cheap GPU hours aren’t enough if capacity sits idle, inference costs destroy margins, or switching providers is prohibitively expensive.

Builders need compute that scales with demand, and the freedom to leave when it stops.

Access gets you started. Orchestration keeps you competitive.

https://io.net/blog/the-state-of-ai-cloud-infrastructure

New open model. No waitlist.

Reflection Beam 1.0 is live on @ionet.

Built for coding and agents. 501B parameters, 23B active, 1M context window.

Start building today.

Anthropic pledges 5% of its shares. Musk pledges a SpaceX share for every kid in America.

Now let’s do the math.

Musk’s works out to roughly $150 a child. Anthropic’s, at a reported IPO value, is under 1% of the $10tn expected to go into the AI build-out.

Good for their brands, yes. Good for the world, less clear.

Rather than giving money away after the fact, keep it from concentrating in the first place.

Opportunity follows access. That’s what @ionet was built for.

$80 billion.

That’s what Anthropic reportedly lost in the first six months of 2026.

Enough to give 80,000 startups $1M of compute each.

Imagine what that many teams could build.

At http://io.net, we’re building for them. GPUs, when you need them, without the high costs or a gigawatt campus

Borrow $1B to buy GPUs.

At 7%, that’s $70M a year in interest.

You owe it whether your GPUs are busy or sitting idle.

So you need them busy.

That pushes providers toward higher prices and longer contracts.

Where your compute comes from changes how your provider treats you.

@ionet puts builders at the center, not complex financing.

The AI build-out is estimated to cost $10.3tn.

That’s roughly 3.6% of US GDP, every year to 2032.

Everyone is funding it. That doesn’t mean everyone gets the compute.

More concrete doesn’t mean more access. Making existing supply accessible does.

That’s what http://io.net was built for.

1 trillion tokens processed.

Yes, trillion.

No inflated narratives. No billion-dollar budgets. No gigawatt campus.

Just GPU capacity, switched on and put to work.

Thank you to every builder who made it happen.

The next trillion comes faster.

23,000 GPUs.

One flagship data centre.

And Microsoft just pulled out because the grid can’t deliver the power until the 2030s.

Money can buy chips and customers, but it can’t speed up a grid connection.

That’s why distributed compute is so important. That’s what @ionet was built for.

The GPU shortage isn’t really a shortage.

It’s a queue.

And the biggest buyers already skipped it.

Everyone else gets the leftovers, a markup and a long lease.

Good thing there’s a shorter line. Compute that’s already built, already running, and priced for the people who actually build.

http://io.net. AI for the many, not the few.

https://io.net/blog/the-ai-oligopoly-four-companies-control-90-of-global-gpu-comput

A few companies control the most powerful AI.

Now they're debating whether it has feelings.

But this is just a way to shift accountability onto the models.

“It’s not us, it’s the AI.”

That’s what concentrated control looks like. A few firms build it, run it, and decide who answers for it.

Open access means more people can build, inspect, and hold it accountable.

That’s why we built http://io.net.