Akash Network

@akashnet

The world's premier decentralized compute marketplace • $AKT Deploy on Akash Console today → akt.fyi/4pDDwVa

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Akash Network
@akashnet
Jul 28
Confidential Compute is officially live on Akash You can now run workloads inside hardware-enforced Trusted Execution Environments (TEEs) to protect your sensitive data and proprietary model weights from infrastructure providers
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Akash Network
@akashnet
Sep 18
The latest University Ambassador cohorts are hosting info-sessions on agents, AkashML inference, and Console deployments. Students building today are choosing their infrastructure for the next decade. Pictured: Cornell Ambassadors in collaboration with Cornell Blockchain.
Akash Student Ambassadors
@AkashStudents
Sep 14
Great kickoff to the semester with @akashnet x @CUBlockchain! @hrishabhayush & @rachelt313 broke down the building blocks of AI agents, introduced students to the Akash ecosystem and Ambassador Program, and wrapped up with a hands-on deployment using Akash Console. A great
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Akash Network
@akashnet
Sep 16
Looking for more RTX 5090s to join the Homenode AI Grid. The new GPU sharing economy is being built right now on Akash. Put your expensive idle compute to work earning a share of the profits. Let the card pay for itself: $0.60/hr right now. 🔗👇
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Akash Network
@akashnet
Sep 14
Introducing Runtime Limits on Akash Console. Renting a GPU for just an hour? No more surprise bills from forgetting to close it down. Set how long a deployment should run when you deploy it, or add one later. The deployment closes when the time is up.
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Akash Network
@akashnet
Sep 11
Companies buying their own GPUs still have to solve for the hours those GPUs sit idle. Akash's marketplace gives owned hardware somewhere to work between workloads, and gives teams a way to add capacity on demand instead of buying ahead of what they need.
Harry Stebbings
@HarryStebbings
Sep 9
Why Every Company Should Buy, Not Rent, GPUs “If I wanted to rent an H100 for a year at $3.50 to $5 an hour across cloud providers, multiplied by 24 hours a day and 365 days a year, I’d end up paying $35,000 to $50,000. But I could buy that same GPU for $30,000.” @cliffweitzman
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