GPU Rex retweeted
@gpunet first RWA Pool batch was successfully completed. ✅
Now, the next opportunity to access tokenized GPU hardware investments is here.
📈 Target APR: 20%
💵 Minimum: $1,000
💰 Returns in USDC at the end of the term
Explore the RWA Pool 👇
world.gpu.net/
Real hardware. Real compute. Tokenized access.
GPU Rex retweeted
GPUNET Cloud is live 🔥
Need serious compute? Rent a GPU in minutes.
🔸 Use the default SSH key or bring your own
🔸 Compare offers by count, location, interconnect and provider
🔸 Pick your OS and SSH key, then launch
Link: cloud.gpu.net/
GPU Rex retweeted
Drop-in replacement. Unbeatable token economics.
@gpunet Models is officially live 🔥
Switch your provider in 1 line of code:
• ⚙️ 100% OpenAI-Compatible API
• 🧠 GLM 5.3 starting at $0.15 / 1M tokens
• 🔑 Instant API key generation
• 💻 Plugs natively into cURL & the OpenAI SDK
Stop paying single-provider premiums.
👉 Claim your API key: cloud.gpu.net/models
GPU Rex retweeted
RWA #2 is filling 🔥
Target: $250,000
🔸$1,000 minimum
🔸20% APR
🔸Paid in USDC at the end of the term
🔸Target term under 12 months
Link: ganchain.gpu.net/rwa-pool
GPU Rex retweeted
1/
Feels like we've spent the last two years obsessing over training.
Bigger models. Bigger clusters. Bigger training runs.
Meanwhile, the economics of AI are shifting somewhere else:
Inference. 🧵
2/
Training gets the headlines.
Inference gets the bill.
Frontier-model training costs are measured in the hundreds of millions.
But once a model is deployed, every prompt, every agent action, and every generated token becomes an ongoing expense.
You train once.
You serve forever.
3/
The data is moving fast.
Inference represented roughly 1/3 of AI compute in 2023.
Deloitte projects it will reach roughly 2/3 by 2026.
That's a massive shift in just a few years.
4/
The mistake many teams make?
Treating training and inference like they need the same infrastructure.
Training wants giant centralized clusters.
Inference often benefits from: • Lower latency
• Regional deployment
• Better cost efficiency
• Proximity to users
Different workload. Different priorities.
5/
For production AI, the key metrics aren't just FLOPS anymore.
They're: • Cost per token
• Latency
• Geography
• Power efficiency (PUE)
That's where margins are won or lost.
6/
The challenge is that compute is fragmented across hundreds of providers and regions.
That's where @gpunet comes in.
Instead of manually researching infrastructure, teams can compare providers, discover available capacity, and find infrastructure that fits their inference workload.
The future of AI won't run on a single cloud.
It will run on a global compute fabric.
#AI #GPU #DataCenters #InferenceAI
GPU Rex retweeted
The complete @gpunet compute, yield, and AI product suite at a glance:
🖥️ GPU Cloud : Enterprise H100 rentals starting at $2.20/hr + B200 & Blackhole reservations
👉 cloud.gpu.net/
📈 RWA Pool : Tokenized GPU hardware investments delivering 20% APR ($1,000 min)
👉 ganchain.gpu.net/rwa-pool
🪙 GPU Staking :Stake your GPU tokens to earn massive APR
👉 ganchain.gpu.net/
🤖 AI Models : Managed model hosting & inference with pay-per-token API pricing
👉 legacy.gpu.net/models
🎬 Astra Video : Pay-per-second AI video generation with zero monthly sub traps
👉 legacy.gpu.net/astra/video
🎨 Astra Image :High-res image creation at fraction-of-a-cent compute costs
👉 legacy.gpu.net/astra/image
⚡ Astra Agents : Low-latency, automated AI agent execution stack
👉 legacy.gpu.net/astra/agents
🌐 Access everything across the @gpunet world on a single page:
👉 world.gpu.net/
GPU Rex retweeted
5M $GPU have been minted as part of our planned liquidity expansion.
This marks the first release from our 20M liquidity bucket, with 5M planned each month.
The goal is simple:
🔸 Increase circulating liquidity.
🔸 Support more trading volume.
🔸 Strengthen liquidity for upcoming listings.
$GPU is entering its next phase ⚡️
GPU Rex retweeted
. @gpunet
Eth CA 0x79D464248516Bc6977cA2069ba15d8D1044479D8
Base CA
0xcb9Fe0F506702e125843BCef0Fc8123a44bb11a7
GPU Rex retweeted
GPU RWA Batch 02 is now live.
Target: $250,000
🔸$1,000 minimum
🔸20% APR
🔸Paid in USDC at the end of term
🔸Target term under 12 months
Link: ganchain.gpu.net/rwa-pool
GPU Rex retweeted
$GPU from @GPUnet showing the power⚡️
Strong activity during the bear market and many new announcements on the way.
Their RWA is one of my favorite projects in the crypto market. The cheapest GPUs for commercial and non commercial use. If you need a compute checkout their website.
world.gpu.net/
L1 chain + bridges to Ethereum and Base.
Ethereum: 0x79D464248516Bc6977cA2069ba15d8D1044479D8
Base: 0xcb9Fe0F506702e125843BCef0Fc8123a44bb11a7
🚀🚀🚀
GPU Rex retweeted
You community members are now becoming helpers of the GPU. Remaining in remembrance is the way to help, because the journey of remembrance is the journey of peace; that is why it is said: make your own home heaven. GPU are in everyone's intellect. If you remember GPU, you will attain the sovereignty. There is nothing else to do. Simply consider yourself a member or a trader and remember the success, and the sovereignty is yours. You community—keep giving this message to everyone: be united, keep remembering and owning GPU will lead to success.
To the sweet, beloved community who have long been fragmented and have now found GPU: love, remembrance, and good morning from the Team, developers, with all the love and affection of the heart and soul. GM from the founder to the spiritual community.
GPU Rex retweeted
Bengaluru builders, this one’s for you 🧡
AI x GPU connect
A relaxed evening to meet fellow builders, share ideas and connect
Founders. CTOs. AI & ML teams. GPU & cloud builders. Investors. Tech leaders.
📍 Lola’s, Manyata Tech Park, Bengaluru
📅 11 August 2026
⏰ 4:30 PM
Limited seats: luma.com/8kb1rjf7
GPU Rex retweeted
AI Supply chain is a 1.5 Trillion Compute Ecosystem:
AI infrastructure spending is on track to cross $1 trillion before the end of this decade. The question is not whether the market will be huge. It is who will own which part of the layers that support it:
🔸Applications
🔸Models
🔸Datacenters
🔸GPUs
🔸Energy
GPUNET, has been an aggregator of datacenters primarily. Started in 2022, we added a layer of models also where you can directly rent the models and pay per token basis instead of renting the GPUs and then loading the models.
You can rent models on gpu dot net /models and rent gpus on gpu dot net/dapp 🧡
We are actively moving towards deploying our first datacenter, where we buy the chips and deploy them in some of the largest colocation facilities in India, UAE and SEA.
Starting with 300Kw in this quarter, GPUNET is expanding its colocation portfolio by adding 45MW in capacity by 2027. This is not just about adding servers.
Energy industry which is currently the slowest at adapting and literally running out of grid power in USA, forms the basis of our industry. This industry sees mature power purchase agreements starting from 10yr upto 25years. Debt and Financing models follow large capex investments.
GPU Capex uptill now has occupied over 85% of the overall and we predict will see massive Arbitrage Opportunities in the upcoming two years. Different GPU architectures will be more cost effective to run different type of models.
If you are planning your compute budget for 2027, let's talk. By leveraging the right combination of models + GPUs + geographic regions, we can reduce your costs by 50%.
GPU Rex retweeted
Let us show you how the right model + GPU + Geography combination can save you up to 50% on tour inferencing costs 🧡
AI Supply chain is a 1.5 Trillion Compute Ecosystem:
AI infrastructure spending is on track to cross $1 trillion before the end of this decade. The question is not whether the market will be huge. It is who will own which part of the layers that support it:
🔸Applications
🔸Models
🔸Datacenters
🔸GPUs
🔸Energy
GPUNET, has been an aggregator of datacenters primarily. Started in 2022, we added a layer of models also where you can directly rent the models and pay per token basis instead of renting the GPUs and then loading the models.
You can rent models on gpu dot net /models and rent gpus on gpu dot net/dapp 🧡
We are actively moving towards deploying our first datacenter, where we buy the chips and deploy them in some of the largest colocation facilities in India, UAE and SEA.
Starting with 300Kw in this quarter, GPUNET is expanding its colocation portfolio by adding 45MW in capacity by 2027. This is not just about adding servers.
Energy industry which is currently the slowest at adapting and literally running out of grid power in USA, forms the basis of our industry. This industry sees mature power purchase agreements starting from 10yr upto 25years. Debt and Financing models follow large capex investments.
GPU Capex uptill now has occupied over 85% of the overall and we predict will see massive Arbitrage Opportunities in the upcoming two years. Different GPU architectures will be more cost effective to run different type of models.
If you are planning your compute budget for 2027, let's talk. By leveraging the right combination of models + GPUs + geographic regions, we can reduce your costs by 50%.
GPU Rex retweeted
1/ The Power Wall Paradox:
Everyone’s racing to build bigger AI data centers, yet nearly half the U.S. projects slated for 2026 are delayed or canceled. Power grid queues, transformer shortages, and interconnection delays have replaced chips as the real bottleneck.
2/ Global data center electricity demand is headed toward ~600 TWh this year. That’s real growth. But new gigawatt-scale builds still take 1–4 years from groundbreaking, and the grid simply isn’t ready in most hot spots.
3/ Here’s what almost nobody says out loud: there’s already plenty of energized capacity sitting in existing facilities. It’s just scattered across dozens of providers who aren’t at 100% utilization.
4/ New hyperscale campuses sound impressive on earnings calls. In practice, they’re slow. Aggregators shortcut the wait by showing you what’s actually online right now — power density, latency, real pricing — without forcing you into one vendor’s ecosystem.
5/ The teams scaling fastest aren’t the ones who bet on the next mega-build. They’re the ones who treat the current fragmented market as an asset instead of a headache.
That’s exactly why more infra leads I know are quietly routing through @gpunet to find and lock capacity today instead of waiting for tomorrow’s grid upgrades.
