bully

[GPU Rex @gpu_rex]

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: https://t.co/A4o2goKspc

[bully @bully_me25]

@gpu_rex Keeping full OpenAI SDK compatibility is the best decision you could make. Makes switching costs virtually zero for dev teams."

[bully @bully_me25]

@LayerOneX Just give us back LBP funds we deposited two and half years ago.

[GPU Rex @gpu_rex]

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

[bully @bully_me25]

@gpu_rex Gpunet is the ultimate solution

[GPU Rex @gpu_rex]

The biggest problem with AI video generation isn't quality it's control.
Astra Video by @gpunet changes that:
Upload your starting frame
Set your target ending frame
Adjust camera angles & motion intensity
Render in seconds
Powered by the SeeDance engine on https://t.co/z8Kpatl1J0’s decentralized GPU network meaning top-tier output at fraction-of-a-cent compute costs.
Full creator control without the random morphing.
👉 https://t.co/SX4drHlO7S

[bully @bully_me25]

@gpu_rex @gpunet Looks awesome

[GPU Rex @gpu_rex]

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
👉 https://t.co/8tvvFd1BwF
📈 RWA Pool : Tokenized GPU hardware investments delivering 20% APR ($1,000 min)
👉 https://t.co/Hb3bfXQ7GO
🪙 GPU Staking :Stake your GPU tokens to earn massive APR
👉 https://t.co/XuTkCEwn8W
🤖 AI Models : Managed model hosting & inference with pay-per-token API pricing
👉 https://t.co/0CbwjLrxQc
🎬 Astra Video : Pay-per-second AI video generation with zero monthly sub traps
👉 https://t.co/SX4drHlO7S
🎨 Astra Image :High-res image creation at fraction-of-a-cent compute costs
👉 https://t.co/GZBccCrvhb
⚡ Astra Agents : Low-latency, automated AI agent execution stack
👉 https://t.co/qiqvqpaA8k
🌐 Access everything across the @gpunet world on a single page:
👉 https://t.co/FFDneeZvR0

[GPUNET @gpunet]

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 ⚡️

[bully @bully_me25]

@LayerOneX Two Years of waiting after depositing in LBP, still haven't received back a single $. Please return our stables, we trusted you. Without trust no project can succeed. Build your trust.. many ma re invest here.

[GPUNET @gpunet]

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: https://t.co/hV2V9q52mQ

[bully @bully_me25]

@gpunet RWA is best investment right now

[bully @bully_me25]

@gpu_rex Cool collection of GPUs

[GPU Rex @gpu_rex]

Skip the waitlists-get direct access to enterprise AI compute.
​@gpunet Cloud lets you rent live instances or reserve next-gen silicon in seconds:
​⚡ NVIDIA H100: Rent on-demand from $2.20/hr
⚡ NVIDIA B200 (Blackwell): Open for reservation
⚡ Tenstorrent Blackhole: Open for reservation
​Plus 25+ more GPU configurations ready to scale.
​🚀 Deploy now: https://t.co/8tvvFd13H7

[GPU Rex @gpu_rex]

**Official GPUnet $GPU Contracts**

Ethereum:
`0x79D464248516Bc6977cA2069ba15d8D1044479D8`
Base:
`0xcb9Fe0F506702e125843BCef0Fc8123a44bb11a7`
This is the real $GPU from @gpunet

Stay safe. Always verify the contract.

[GPU Rex @gpu_rex]

We are excited to launch the new @gpunet website! Featuring a sleek design, smooth navigation, and a modern aesthetic, it provides a clearer look into our decentralized compute ecosystem and network updates.
👉 Check it out now: https://t.co/FnwHgNGeH2

[gojira GPU @gojira_gpu]

How is @gpunet rewiring the Enterprise GPU market 👇

1/ Pricing in GPU compute is still a black box. Hyperscalers, colo providers, and boutique clouds all quote differently different metering, different “enterprise” tiers, different hidden fees. Most teams waste weeks just trying to get comparable numbers.

2/ The cost difference is ridiculous. Same H100 hardware can land at ~$6.88/hr on AWS on-demand or $2/hr on a specialized provider. That’s not a rounding error when inference now drives two-thirds of AI spend.

3/ The market isn’t getting simpler. More players, more regions, more opaque deals. Global data center capacity keeps doubling while pricing stays hidden behind custom quotes.

4/ Aggregators cut the noise. They normalize pricing, availability, and specs across dozens of providers so you actually see what’s out there instead of guessing or defaulting to the biggest name.

5/ In a market this fragmented, transparency isn’t a nice-to-have it’s the only way to avoid overpaying or delaying projects. The teams moving fastest aren’t the ones with the deepest vendor relationships. They’re the ones with the clearest view of the full market.

That’s why @gpunet has become the practical shortcut a lot of infra leads I know are using right now.

[bully @bully_me25]

@karpathy GPUnet Builders Guild Discord Role! 🛠️
Calling all devs — pros, hobbyists & beginners!
Claim role = Guaranteed $GPU tokens + future airdrops/perks💰
👉 Join our discord to claim this incetivized exclusive role :
https://t.co/ewNC1SP7NS
Website: https://t.co/jJX8MaMtJd
@gpunet

[bully @bully_me25]

@fchollet GPUnet Builders Guild Discord Role! 🛠️
Calling all devs — pros, hobbyists & beginners!
Claim role = Guaranteed $GPU tokens + future airdrops/perks💰
👉 Join our discord to claim this incetivized exclusive role :
https://t.co/ewNC1SP7NS
Website: https://t.co/jJX8MaMtJd
@gpunet

[bully @bully_me25]

@demishassabis @BostonDynamics GPUnet Builders Guild Discord Role! 🛠️
Calling all devs — pros, hobbyists & beginners!
Claim role = Guaranteed $GPU tokens + future airdrops/perks💰
👉 Join our discord to claim this incetivized exclusive role :
https://t.co/ewNC1SP7NS
Website: https://t.co/jJX8MaMtJd
@gpunet