zerokn0wledge

io.net thesis: decentralized GPU network and a $10B FDV case

Thread749 words
Bullish call$IO−96%since listing, moved against the callHow it played out ↓

Bull case for io.net clustering idle GPUs from data centers, miners and consumer devices to serve AI/ML inference at a fraction of cloud cost. Cites compute demand rising 10x every 18 months and OpenAI's $700K+ daily cost, and expects over $10B FDV at peak.

Key claims
AI compute demand rises 10x every 18 months
OpenAI spends $700K+ per day on ChatGPT compute
IO can exceed $10B FDV in the bull
The $IO token & airdrop are close and it will be one of the largest launches of the year. @ionet will be a leader of the AI narrative throughout the cycle, easily worth > $10B in the bull. Time to give you the alpha-summary you need to position yourself. 🧵👇 t.co/mNSJ5Mr49e 1/ AI/ML is a market in a state of hyper-growth. Currently the compute demand from AI applications is increasing 10x every 18 months (and growing rapidly). This comes with a 3'100% annual increase in model training and inference cost for AI companies. 2/ This is due to a shortage on the GPU market. If you can address that supply shortage and serve this hyper-growth market, you will capture a lot of value. That's what @ionet_official does (and a lot more). 3/ The GPU shortage causes: ✦ Long lead times: Weeks to access GPUs in centralized cloud services ✦ Limited choice: Little choice over GPU hardware, location, security or latency ✦ High costs: OpenAI spends $700K+ per day running ChatGPT on centralized cloud servers 4/ @ionet_official fixes this. But let's look at the "how" a bit closer. Most of the GPU supply globally is underutilized. It sits in sources like independent data centers, crypto mining farms, and consumer GPUs. 5/ @ionet_official clusters that idle GPU capacity from different sources & multiple locations. This allows users (AI/ML company) to access computing power at a fraction of the cost of traditional cloud providers and benefit from greater customizability. x.com/TradingAloha/status/1765137851422044591?t=nlOUD4AgVl9AEPoYBCdD_A&s=19 6/ @ionet_official is purpose-built to support low latency & high demand use cases like AI/ML inference. Through parallel processing @ionet_official can cluster tens of 1000s of distributed GPUs together instead of just a few (like most competitors). 7/ It's the only network able to support AI/ML workloads and @rendernetwork as a comparable is therefore using @ionet to serve These use cases and supplies GPU power to the network. 8/ As the largest decentralized GPU network, @ionet is likely due for a huge valuation. @alpha_pls has recently put out a great thread on this! 👇 x.com/alpha_pls/status/1779793606150103516 9/ If you want to really dive deep, this thread by @jake_pahor is for you! 👇 x.com/jake_pahor/status/1767687030052643225?s=20 10/ Another great one is this masterpiece by @eli5defi! 👇 x.com/eli5_defi/status/1768261338298794126?s=20 11/ Finally, there is my own deep-dive thread which you can find right here! 👇 x.com/zerokn0wledge_/status/1765407029764767858?s=46 12/ If you want to hear what the COO @MTorygreen himself has to say, check @alpha_pls' interview with him here! 👇 x.com/alpha_pls/status/1765123537654943841 13/ But GPU-as-a-Service is not all. The network of high performance nodes that is what underlies this stack, can be used to bootstrap independent decentralized networks that run arbitrary IO Elements on top of them. A whole ecosystem of scalable, app-specific AI chains anon. 14/ Do you see what my thesis amounts to here? And this is not just your average AI "vaporware". @ionet_official has found real-world adoption and is generating revenue as the market leader in a high-growth market already. 15/ This is evidenced by the numbers: x.com/zerokn0wledge_/status/1777054002167091332 16/ Which already results in significant revenue that is generated. 17/ And just to put this into perspective, the GPU market is huge, anon! There is so much room for growth here. x.com/flowslikeosmo/status/1776626044998668319?s=46&t=LqJgJfWjl0dXj8hmReuSuw 18/ Okay cool, but how can you get involved? Hopefully, you are already part of @ionet's Ignition Program. If not, hurry up. Details by @eli5defi below. x.com/eli5_defi/status/1770803022475485427?s=20 19/ Why you should care about this is something that @Deebs_DeFi brings to the point very concisely here! 👇 x.com/deebs_defi/status/1768645294902624752?s=46&t=ybX5dOdpOgujlOkXmLXfnA 20/ @Deebs_DeFi also put out a great speed run guide to set up your GPU worker! 👇 x.com/Deebs_DeFi/status/1776610164965257273 21/ I did the same, for Apple users to set up CPU workers here! 👇 x.com/zerokn0wledge_/status/1774364782147354885 22/ If you're looking for the maths on what the airdrop might be worth, have a look at the rundown below! 👇 x.com/Deebs_DeFi/status/1774113862830473333 23/ Maybe you're skeptical of why this needs to have anything to do with crypto, but believe me, there are interesting opportunities. Learn more here! 👇 x.com/sterlingcrispin/status/1765095532446261688?t=8Lvn5qLYr8gyl1WDSYYqLQ&s=19 24/ I think overall the bull case here is very clear. @ionet will be a giant in the DePIN/AI space. During peak bull, I can see this exceed $10B FDV easily, which will make this one of the largest launches of the year. DYOR and position yourself anon. Don't fade. That's a wrap! I hope you've found this thread helpful! 🫡 Make sure to follow me @zerokn0wledge_ to stay ahead of the curve on DePIN / AI game! Like/Repost of the below post is also highly appreciated! 🙏👇

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How the call played out · since 17 Apr 2024

Prices as of 23 Oct 2026

This piece takes a view on $IO, so that move is read against the call.

$IOio.netBullish thesis

io.net clusters idle GPUs to serve AI inference at a fraction of cloud cost while AI compute demand grows far faster than supply.

−96%
Moved against the call · since it listed on 12 Jun 2024, 8 weeks after this piece
At listing
$4.17
Now
$0.159
vs BTC
−97%
After 1 month
−41%
After 3 months
−60%
After 1 year
−81%
High since
+36% 13 Jun 2024
Low since
−98% 06 Apr 2026

Daily closes in USD from DefiLlama and Yahoo Finance. Only a bullish or bearish call in a thesis or market take is tracked; explainers, lists, maps and mentions are neutral context. Not financial advice.

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