Parallax by Gradient
Host LLMs across devices sharing GPU to make your AI go brrr
835 followers
Host LLMs across devices sharing GPU to make your AI go brrr
835 followers
Your local AI just leveled up to multiplayer. Parallax is the easiest way to build your own AI cluster to run the best large language models across devices, no matter their specs or location.
Its an amazing concept, I stumbled upon Parallex today and now setting up all my systems with GPUs together so I can make use of private AI.
The Chat UI is pretty basic but I guess its only for demo. Are you working on adding maybe the Reasoning/Thinking/Files/Modality to it?
If not I would be happy to collaborate and chat with you as I am setting up local AI chatbot with all the tools/efficiencies while running different models in a a local environment.
Parallax by Gradient
Hi everyone, this is Eric, co-founder of Gradient.
The Gradient team behind Parallax is a group of engineers and scientists driven by a shared belief that open intelligence will be one of humanity’s most important assets.
And that’s why we are working on foundation models and rebuilding the training & serving stacks to push the frontier of open intelligence.
In short, Gradient focuses on the creation and delivery of open intelligence.
Parallax is our first step in making access to intelligence feel as easy turning on a light.
And we have a lot more exciting stuff coming up so stay tuned!
To contribute to Parallax: https://github.com/GradientHQ/parallax
To learn more about us: https://gradient.network
Congrats on shipping this!
The messaging is sharp; I mean, ‘AI goes brrr’ has substance behind it. Love it!
Distributed compute made simple is a killer value prop if you nail onboarding and clarity around use cases.
Parallax by Gradient
@nosheen_kanwal Great suggestion! Feel free to reach out to us anytime！
@joysong_j Thanks, and sure. What is the best way to stay in touch?
Just followed you on LinkedIn
Mom Clock
Excited to hunt Parallax today!
It’s the first framework I’ve seen that makes distributed local inference feel effortless — no more GPU bottlenecks. Big milestone for open intelligence, congrats Gradient team 👏
Parallax by Gradient
@justin2025 Thank you for hunting Parallax and for the kind words!
That's exactly what we target to deliver with Parallax: a unified and scalable experience to power your sovereign AI modes and applications.
What we are especially proud of:
3 modes, 1 fabric, all sovereign. Local host with a single machine; Co-Host over LAN with friends and teammates; Global Host on a wide area network (WAN) across locations.
Deploy on a Mac+PC mix, no public IP required, traceable runs end to end.
Supporting 40+ open models on launch, from 0.6B to trillion-class MoE.
We would love to hear what you build and what can be made smoother. Issues and PRs welcome.
Thanks for helping push open intelligence forward with us!
Parallax by Gradient
@adamy_gn So happy to launch Parallax yesterday!
Mom Clock
@adamy_gn Yeah, I happen to have a Mac Mini M1 idle, it will be my homework tonight :D
Parallax by Gradient
@justin2025 niiiiice!
Let us know how it goes🚀
RewriteBar
This is cool! Is it also possible to connect the GPU to the public network so that it can be accessed remotely from different locations?
Happycapy
This concept is fantastic! The ability to overcome obstacles and act without limitations perfectly matches my vision of modern work environment! Congrats Gradient team 👏
This is a fantastic concept.
It immediately sparked an idea: What if you added an incentive layer or a token economy on top of this?
Users could contribute their idle hardware (GPUs) to the global network and earn tokens based on the compute power they provide. These tokens could then be used by other users to "pay" for their inference tasks on the network.
This would turn Parallax from a collaborative tool for trusted peers (friends, teammates) into a fully decentralized, global marketplace for AI compute. It seems like the logical next step to truly ensure "no one will ever be GPU-poor again!"
Great work by the Gradient team!
Parallax by Gradient
@samsc Awesome idea! Who knows, it might come to be in the future!