We’ve been building @crynuxio for years, one step at a time.
It starts by connecting underutilized compute from people around the world to the network, allowing anyone to contribute GPU resources while developers access AI inference through a simple API.
This isn’t another GPU rental marketplace.
Traditional GPU marketplaces require users to rent specific hardware, creating trust and verification challenges. With Crynux, developers don’t request a particular GPU. They submit an AI inference task with requirements like latency and price, and the network automatically routes it to the best available compute provider.
The result is a permissionless AI inference marketplace focused on outcomes, not hardware.
Whether you’re contributing a single gaming GPU at home or operating a larger compute cluster, you can participate. Many of our providers today are individuals running GPUs from their homes, helping build a decentralized AI network from the ground up.
Community-powered infrastructure. Community-owned compute. Decentralized AI.
Everyone is talking about how great artificial intelligence is
but no one is asking who is in control. Most often, the technologies are in the hands of corporations. Should it continue to be this way? 🧵👇
The Crynux Thread Contest is officially closed.
Thank you to everyone who participated and took the time to create and share content about Crynux.
We’re reviewing all submissions now. Winners will be announced by the end of next week.
Good luck to everyone who entered!
𝑻𝒐𝒅𝒂𝒚, 𝒎𝒐𝒔𝒕 𝑨𝑰 𝒓𝒖𝒏𝒔 𝒐𝒏 𝒊𝒏𝒇𝒓𝒂𝒔𝒕𝒓𝒖𝒄𝒕𝒖𝒓𝒆 𝒄𝒐𝒏𝒕𝒓𝒐𝒍𝒍𝒆𝒅 𝒃𝒚 𝒂 𝒉𝒂𝒏𝒅𝒇𝒖𝒍 𝒐𝒇 𝒄𝒐𝒎𝒑𝒂𝒏𝒊𝒆𝒔. 𝑭𝒆𝒘 𝒑𝒆𝒐𝒑𝒍𝒆 𝒓𝒆𝒂𝒍𝒊𝒛𝒆 𝒘𝒉𝒂𝒕 𝒕𝒉𝒂𝒕 𝒄𝒐𝒖𝒍𝒅 𝒎𝒆𝒂𝒏 𝒇𝒐𝒓 𝒕𝒉𝒆 𝒇𝒖𝒕𝒖𝒓𝒆 𝒐𝒇 𝑨𝑰.
Every time you ask an AI a question, generate an image, or build an AI-powered app, there's a good chance the computing power behind it comes from the same small group of providers.
That raises an important question.
What happens when the technology shaping the future of humanity depends on infrastructure owned by only a few organizations?
Who decides the price of compute? Who decides who gets access? And as AI demand explodes, can the current model keep up?
A growing number of builders believe the answer isn't bigger data centers it's a completely different way of powering AI.
And if that alternative works, it could completely change who gets to build, own, and benefit from the next generation of AI.
Let's explore how.
🧵🔻
$TIBBIR was called early and went on to pull ridiculous X's with some great lore.
now take a look at $CNX / @crynuxio.
a brand new DeAI project sitting at under a $1m market cap.
people ask what separates @crynuxio from the dozens of other DeAI projects. the answer starts with the people building it.
one example is core developer Aaron Yuasa (@0xaaaaaron):
🔹 10 years as an ML engineer at Google AI
🔹 built production systems handling billions of daily requests
🔹 10+ publications and patents across LLMs and distributed machine learning
🔹 focused on reducing compute costs for large-scale AI infrastructure
then there's Luke Weber.
8+ years working across blockchain, ZK and MPC, with multiple patents and publications. he also built one of the world's first open-source blockchain AI frameworks back in 2019.
the whole team behind @crynuxio are veterans of the game with years of experience building at the highest level for decades.
study. invest in teams.
@base ca: 0x9557DD9E241bc9636732623B672B4090AF519396
laura runs a small experiment out of her bedroom in a town most maps don't bother labeling.
she's training an AI to look at photos of crops and catch diseases before it spreads.
good idea.
real problem.
the farmers are waiting for it .
But every time she gets close, she hits the same wall: the computers powerful enough to do the work belong to someone else.
a thread 🧵🔻
7 companies control virtually ALL the compute powering AI today.
They set the prices.
They decide who gets access.
They can cut you off with a policy change.
And you have zero way to verify your requests were actually processed.
This isn't just unfair it's dangerous.
What if AI ran on thousands of edge devices instead gaming PCs, workstations, even phones owned by regular people worldwide?
It's already live with:
⇒ 298,000+ tasks completed
⇒ 229+ nodes online
⇒ Production mainnet, not a whitepaper.
This is @crynuxio .
Here's exactly how it works. $CNX
@HenriqueLampert there’s a full rust sdk named argent-runtime. see demos in the playground:
most simple - https://t.co/6VxjgwmvD3
most complex (dex) - https://t.co/SJITuXkFbe
That’s a longer-horizon effort and is exactly what hashdag is “hunting” for. But everything above Kaspa will ultimately be built over covenants, including the soon coming based-apps mvp and future vprogs and any staghunt implemented on any of them, so now is the time to celebrate that new raw native expressiveness and harness it. Also, don’t underestimate native atomic composability using covenants. Though I don’t think we’ll reach completely novel usecases at the first stage, the inherent superiorities of Kaspa as infrastructure, can make classic usecases shine again and show ppl how they look like on a true and fair crypto platform. Another point is agentic software, I think covenants as compressed atomically-deployed onchain contracts are much better suited for this economy. Everything you see on eg https://t.co/v1HN4flEVB is ppl discussing specs bcs they ack this potential
AI shouldn’t be limited by high compute costs or closed infrastructure.
Open models + decentralized compute unlock lower costs, greater accessibility, and AI infrastructure that isn’t controlled by a handful of providers.
That’s why we built Crynux.
$CNX
Everyone is talking about building smarter AI.
Almost no one is talking about what AI quietly depends on every single second.
Imagine opening your favorite streaming app and pressing play.
The movie doesn't appear by magic.
Behind that one click are thousands of computers working together to deliver it to your screen.
AI works the same way.
Every question you ask, every image it creates, every line of code it writes needs computing power somewhere.
Now imagine if most of that computing power belonged to only a handful of companies.
If they have an outage, increase prices, or decide who gets access, millions of developers and businesses are affected even if their AI models haven't changed.
That's the hidden problem most people never see.
The future of AI isn't only about building better models.
It's also about building a better way to power them.
And that's exactly where @crynuxio enters the story... 👇
been renting GPU compute from the usual suspects for a while now, always hated paying premium just to trust a company i can't verify anything from
@crynuxio just went from testnet to actual mainnet (lithium), so i decided to dig in
🧵 $CNX