Kenny Grey
136 Publications
Kenny Grey
Signaler
Bloquer l’utilisateur
My name is Kenny Grey, a crypto enthusiast and a copy writer. I hope my contents speaks more of me.
8 Suivis
60 Abonnés
161 J’aime
Publications
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Vidéos
·
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Haussier
The next AI breakthrough won't just depend on better models, it will depend on better infrastructure and that's where decentralized GPU marketplaces are beginning to change the conversation.
Yet, getting access to GPUs is still frustratingly expensive, fragmented, and often controlled by a handful of hyperscalers.
What if there was a better way?
That's exactly why I find Fluence's decentralized GPU marketplace so compelling.
Instead of forcing developers to juggle multiple cloud platforms or depend on a single provider, @fluence brings GPU capacity from multiple providers together under one deployment layer.
That means you can launch, manage, and scale workloads with greater flexibility while avoiding the limitations of traditional cloud infrastructure.
As AI adoption accelerates, access to compute shouldn't be a privilege controlled by a few companies. It should be open, competitive, and accessible to everyone building the next generation of applications.
The future of compute isn't about choosing one cloud over another, it's about moving beyond hyper-scalers. That's the vision Fluence is bringing to life, and it's one I'm excited to see unfold. 🌐⚡
The next AI breakthrough won't just depend on better models, it will depend on better infrastructure and that's where decentralized GPU marketplaces are beginning to change the conversation.
Yet, getting access to GPUs is still frustratingly expensive, fragmented, and often controlled by a handful of hyperscalers.
What if there was a better way?
That's exactly why I find Fluence's decentralized GPU marketplace so compelling.
Instead of forcing developers to juggle multiple cloud platforms or depend on a single provider, @Fluence brings GPU capacity from multiple providers together under one deployment layer.
That means you can launch, manage, and scale workloads with greater flexibility while avoiding the limitations of traditional cloud infrastructure.
As AI adoption accelerates, access to compute shouldn't be a privilege controlled by a few companies. It should be open, competitive, and accessible to everyone building the next generation of applications.
The future of compute isn't about choosing one cloud over another, it's about moving beyond hyper-scalers. That's the vision Fluence is bringing to life, and it's one I'm excited to see unfold. 🌐⚡
Yet, getting access to GPUs is still frustratingly expensive, fragmented, and often controlled by a handful of hyperscalers.
What if there was a better way?
That's exactly why I find Fluence's decentralized GPU marketplace so compelling.
Instead of forcing developers to juggle multiple cloud platforms or depend on a single provider, @Fluence brings GPU capacity from multiple providers together under one deployment layer.
That means you can launch, manage, and scale workloads with greater flexibility while avoiding the limitations of traditional cloud infrastructure.
As AI adoption accelerates, access to compute shouldn't be a privilege controlled by a few companies. It should be open, competitive, and accessible to everyone building the next generation of applications.
The future of compute isn't about choosing one cloud over another, it's about moving beyond hyper-scalers. That's the vision Fluence is bringing to life, and it's one I'm excited to see unfold. 🌐⚡
53
·
--
Haussier
We're at a point where many developers and businesses are questioning the status quo. Why should launching an application mean committing to a single cloud provider, unpredictable costs, and infrastructure that's difficult to move away from?
That's why Cloudless Computing is such an exciting shift.
Looking at what @fluence is building, it's clear the focus isn't just on decentralization for the sake of it, it's about giving developers real freedom.
Predictable hourly billing, no vendor lock-in, and the ability to launch GPU instances anywhere from a single console make infrastructure simpler and more flexible.
Instead of adapting your workload to fit a cloud provider, you choose the provider that fits your workload. That's how it should have been from the start.
As AI, Web3, and high-performance computing continue to grow, open and transparent infrastructure will become more important than ever. Fluence is proving that the future of compute doesn't have to be controlled by a handful of cloud giants.
Cloudless on your terms. That's a vision worth paying attention to. 🌐⚡
We're at a point where many developers and businesses are questioning the status quo. Why should launching an application mean committing to a single cloud provider, unpredictable costs, and infrastructure that's difficult to move away from?
That's why Cloudless Computing is such an exciting shift.
Looking at what @Fluence is building, it's clear the focus isn't just on decentralization for the sake of it, it's about giving developers real freedom.
Predictable hourly billing, no vendor lock-in, and the ability to launch GPU instances anywhere from a single console make infrastructure simpler and more flexible.
Instead of adapting your workload to fit a cloud provider, you choose the provider that fits your workload. That's how it should have been from the start.
As AI, Web3, and high-performance computing continue to grow, open and transparent infrastructure will become more important than ever. Fluence is proving that the future of compute doesn't have to be controlled by a handful of cloud giants.
Cloudless on your terms. That's a vision worth paying attention to. 🌐⚡
That's why Cloudless Computing is such an exciting shift.
Looking at what @Fluence is building, it's clear the focus isn't just on decentralization for the sake of it, it's about giving developers real freedom.
Predictable hourly billing, no vendor lock-in, and the ability to launch GPU instances anywhere from a single console make infrastructure simpler and more flexible.
Instead of adapting your workload to fit a cloud provider, you choose the provider that fits your workload. That's how it should have been from the start.
As AI, Web3, and high-performance computing continue to grow, open and transparent infrastructure will become more important than ever. Fluence is proving that the future of compute doesn't have to be controlled by a handful of cloud giants.
Cloudless on your terms. That's a vision worth paying attention to. 🌐⚡
83
·
--
Haussier
If you’ve been watching the DePIN (Decentralized Physical Infrastructure Networks) space lately, you’ve probably noticed a major shift. We are no longer just looking at individual altcoins; we are watching the total unbundling of the traditional cloud (AWS, Google Cloud) into a decentralized, open-source stack.
Looking at DIMO, Dynex, GPUnet, and Fluence, a very clear picture of this new Decentralized Cloud is starting to emerge.
🧠 The Shared Trend: DePIN for AI and Data
What stands out is that these projects are building a verticalized cloud. In the Web2 world, infrastructure specialized into CDNs, data warehouses, and serverless platforms.
We are seeing that exact same specialization happen in Web3:
Specialized Hardware is King: Whether it's cars on the road ($DIMO) or GPUs in data centers ($GPUnet/$DNX), the supply is being pooled on-chain to break centralized monopolies.
AI as the Engine: You need vehicle data to train models, GPUs to run them, and a runtime to host the AI agents. These projects are the fuel and the engine for the AI revolution.
💡 WHY FLUENCE STANDS OUT:
The "Logical" Layer
While most DePIN projects focus on the "physical" (hotspots, sensors, GPUs), Fluence is building the Logical Layer.
Fluence's mission is to provide a "Cloudless" backend. It doesn't want to just sell you a server; it wants to give you a decentralized version of AWS Lambda.
Instead of renting a specific machine and managing it yourself, Fluence allows developers to deploy functions and services into a global marketplace. It acts as the Glue that connects raw resources:
An AI pipeline could pull data from DIMO...
Process it using a job on GPUnet...
And expose the final API through a service running on Fluence.
🌍 Summary: A Permissionless Future
The pattern here is clear: Web3 is moving away from purely financial memes and toward token-coordinated utility. Fluence is positioning itself as the neutral coordination plane where these physical resources become usable by developers.
If you’ve been watching the DePIN (Decentralized Physical Infrastructure Networks) space lately, you’ve probably noticed a major shift. We are no longer just looking at individual altcoins; we are watching the total unbundling of the traditional cloud (AWS, Google Cloud) into a decentralized, open-source stack.
Looking at DIMO, Dynex, GPUnet, and Fluence, a very clear picture of this new Decentralized Cloud is starting to emerge.
🧠 The Shared Trend: DePIN for AI and Data
What stands out is that these projects are building a verticalized cloud. In the Web2 world, infrastructure specialized into CDNs, data warehouses, and serverless platforms.
We are seeing that exact same specialization happen in Web3:
Specialized Hardware is King: Whether it's cars on the road ($DIMO) or GPUs in data centers ($GPUnet/$DNX), the supply is being pooled on-chain to break centralized monopolies.
AI as the Engine: You need vehicle data to train models, GPUs to run them, and a runtime to host the AI agents. These projects are the fuel and the engine for the AI revolution.
💡 WHY FLUENCE STANDS OUT:
The "Logical" Layer
While most DePIN projects focus on the "physical" (hotspots, sensors, GPUs), Fluence is building the Logical Layer.
Fluence's mission is to provide a "Cloudless" backend. It doesn't want to just sell you a server; it wants to give you a decentralized version of AWS Lambda.
Instead of renting a specific machine and managing it yourself, Fluence allows developers to deploy functions and services into a global marketplace. It acts as the Glue that connects raw resources:
An AI pipeline could pull data from DIMO...
Process it using a job on GPUnet...
And expose the final API through a service running on Fluence.
🌍 Summary: A Permissionless Future
The pattern here is clear: Web3 is moving away from purely financial memes and toward token-coordinated utility. Fluence is positioning itself as the neutral coordination plane where these physical resources become usable by developers.
Looking at DIMO, Dynex, GPUnet, and Fluence, a very clear picture of this new Decentralized Cloud is starting to emerge.
🧠 The Shared Trend: DePIN for AI and Data
What stands out is that these projects are building a verticalized cloud. In the Web2 world, infrastructure specialized into CDNs, data warehouses, and serverless platforms.
We are seeing that exact same specialization happen in Web3:
Specialized Hardware is King: Whether it's cars on the road ($DIMO) or GPUs in data centers ($GPUnet/$DNX), the supply is being pooled on-chain to break centralized monopolies.
AI as the Engine: You need vehicle data to train models, GPUs to run them, and a runtime to host the AI agents. These projects are the fuel and the engine for the AI revolution.
💡 WHY FLUENCE STANDS OUT:
The "Logical" Layer
While most DePIN projects focus on the "physical" (hotspots, sensors, GPUs), Fluence is building the Logical Layer.
Fluence's mission is to provide a "Cloudless" backend. It doesn't want to just sell you a server; it wants to give you a decentralized version of AWS Lambda.
Instead of renting a specific machine and managing it yourself, Fluence allows developers to deploy functions and services into a global marketplace. It acts as the Glue that connects raw resources:
An AI pipeline could pull data from DIMO...
Process it using a job on GPUnet...
And expose the final API through a service running on Fluence.
🌍 Summary: A Permissionless Future
The pattern here is clear: Web3 is moving away from purely financial memes and toward token-coordinated utility. Fluence is positioning itself as the neutral coordination plane where these physical resources become usable by developers.
40
·
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Sometimes the hardest part of building AI infrastructure isn’t the model, it’s choosing the right hardware to run it.
That’s something I like about what @fluence is doing here. Instead of leaving developers guessing which GPU fits their workload, they’ve made it easier to match use cases with the right compute power.
Instead of stitching together multiple compute solutions, the idea is simple, choose the workload, pick the GPU, and deploy.
For anyone building AI agents, training models, or running inference pipelines, having this level of clarity around compute options can save a lot of trial and error.
Sometimes better infrastructure isn’t about adding more tools, it’s about making the right ones easier to use.
🚀
👉
http://fluence.network
Sometimes the hardest part of building AI infrastructure isn’t the model, it’s choosing the right hardware to run it.
That’s something I like about what @Fluence is doing here. Instead of leaving developers guessing which GPU fits their workload, they’ve made it easier to match use cases with the right compute power.
Instead of stitching together multiple compute solutions, the idea is simple, choose the workload, pick the GPU, and deploy.
For anyone building AI agents, training models, or running inference pipelines, having this level of clarity around compute options can save a lot of trial and error.
Sometimes better infrastructure isn’t about adding more tools, it’s about making the right ones easier to use.
🚀
👉
http://fluence.network
That’s something I like about what @Fluence is doing here. Instead of leaving developers guessing which GPU fits their workload, they’ve made it easier to match use cases with the right compute power.
Instead of stitching together multiple compute solutions, the idea is simple, choose the workload, pick the GPU, and deploy.
For anyone building AI agents, training models, or running inference pipelines, having this level of clarity around compute options can save a lot of trial and error.
Sometimes better infrastructure isn’t about adding more tools, it’s about making the right ones easier to use.
🚀
👉
http://fluence.network
75
·
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Haussier
The Future of AI Infrastructure Is Finally Here, and It Is Called Fluence.
If you have ever tried running AI agents at scale, you already know the headache. You end up stitching together five different compute products, managing vendor relationships across the board, and still somehow paying through the nose for every gigabyte of data that moves. @fluence is changing all of that, and the approach is refreshingly straightforward.
What Fluence Actually Does?
Fluence gives AI developers the infrastructure primitives they need to run agents reliably, all in one place. No more assembling a Frankenstein stack. Instead, you get four tightly integrated building blocks that cover everything from logic to inference.
These are always on and built for the long haul, meaning your agents never go dark at the worst possible moment. On-Demand Inference (GPU) is the clever part. Rather than burning money on GPU compute around the clock, your agents connect to GPU containers only when they actually need them.
You can even serve your own models to slash API costs and cut latency. Pay for what you use, not for what sits idle.
No Vendor Lock-In might be the most underrated feature on this list. Fluence deploys across Tier 3 and 4 datacenters globally, letting you mix and match providers, regions, and hardware as you see fit.
Zero Egress Fees is the one that will make most developers do a double take. AI agents move enormous volumes of data, and most cloud providers treat outbound bandwidth like a premium product. Fluence does not tax it. Bandwidth is unlimited, and pricing is flat rate, daily for CPUs and hourly for GPUs.
At just $10.78 per month for a setup with 2 vCPUs, 4 GB RAM, and 25 GB Storage, the barrier to entry is genuinely low. This is the kind of infrastructure pricing that makes serious AI development accessible to builders who are not yet backed by a Series B round.
The honest takeaway? Fluence is building the plumbing that the AI agent era actually needs.
The Future of AI Infrastructure Is Finally Here, and It Is Called Fluence.
If you have ever tried running AI agents at scale, you already know the headache. You end up stitching together five different compute products, managing vendor relationships across the board, and still somehow paying through the nose for every gigabyte of data that moves. @Fluence is changing all of that, and the approach is refreshingly straightforward.
What Fluence Actually Does?
Fluence gives AI developers the infrastructure primitives they need to run agents reliably, all in one place. No more assembling a Frankenstein stack. Instead, you get four tightly integrated building blocks that cover everything from logic to inference.
These are always on and built for the long haul, meaning your agents never go dark at the worst possible moment. On-Demand Inference (GPU) is the clever part. Rather than burning money on GPU compute around the clock, your agents connect to GPU containers only when they actually need them.
You can even serve your own models to slash API costs and cut latency. Pay for what you use, not for what sits idle.
No Vendor Lock-In might be the most underrated feature on this list. Fluence deploys across Tier 3 and 4 datacenters globally, letting you mix and match providers, regions, and hardware as you see fit.
Zero Egress Fees is the one that will make most developers do a double take. AI agents move enormous volumes of data, and most cloud providers treat outbound bandwidth like a premium product. Fluence does not tax it. Bandwidth is unlimited, and pricing is flat rate, daily for CPUs and hourly for GPUs.
At just $10.78 per month for a setup with 2 vCPUs, 4 GB RAM, and 25 GB Storage, the barrier to entry is genuinely low. This is the kind of infrastructure pricing that makes serious AI development accessible to builders who are not yet backed by a Series B round.
The honest takeaway? Fluence is building the plumbing that the AI agent era actually needs.
If you have ever tried running AI agents at scale, you already know the headache. You end up stitching together five different compute products, managing vendor relationships across the board, and still somehow paying through the nose for every gigabyte of data that moves. @Fluence is changing all of that, and the approach is refreshingly straightforward.
What Fluence Actually Does?
Fluence gives AI developers the infrastructure primitives they need to run agents reliably, all in one place. No more assembling a Frankenstein stack. Instead, you get four tightly integrated building blocks that cover everything from logic to inference.
These are always on and built for the long haul, meaning your agents never go dark at the worst possible moment. On-Demand Inference (GPU) is the clever part. Rather than burning money on GPU compute around the clock, your agents connect to GPU containers only when they actually need them.
You can even serve your own models to slash API costs and cut latency. Pay for what you use, not for what sits idle.
No Vendor Lock-In might be the most underrated feature on this list. Fluence deploys across Tier 3 and 4 datacenters globally, letting you mix and match providers, regions, and hardware as you see fit.
Zero Egress Fees is the one that will make most developers do a double take. AI agents move enormous volumes of data, and most cloud providers treat outbound bandwidth like a premium product. Fluence does not tax it. Bandwidth is unlimited, and pricing is flat rate, daily for CPUs and hourly for GPUs.
At just $10.78 per month for a setup with 2 vCPUs, 4 GB RAM, and 25 GB Storage, the barrier to entry is genuinely low. This is the kind of infrastructure pricing that makes serious AI development accessible to builders who are not yet backed by a Series B round.
The honest takeaway? Fluence is building the plumbing that the AI agent era actually needs.
62
·
--
Haussier
☁ What if your cloud bill was actually affordable?
Most people just accept that running servers in the cloud is expensive. AWS charges you. DigitalOcean charges you. And you just, pay it, month after month, because what choice do you have?
Fluence just made that question a lot more interesting to answer.
Here is what the numbers actually look like for a 2 vCPU, 4 GB RAM, 25 GB Storage instance:
🔸AWS will take $69.50 from you every single month.
🔸DigitalOcean asks for $42.00.
🔸Hetzner brings it down to $17.60.
@fluence ? Just $10.78.
That is not a rounding error. That is a 84% saving compared to AWS for the exact same instance specs. Even against Hetzner, widely known as one of the most budget friendly providers in the game, Fluence still comes out ahead.
What makes this even more compelling is the pricing calculator built right into their homepage. You pick your instance type, slide the additional storage and RAM controls to match your actual needs, and watch your real monthly cost update live.
For developers, startups, and indie builders who are tired of cloud bills eating their runway before their product even finds users, this is worth a serious look.
The decentralised compute era is here, and apparently it also comes with receipts.
Visit fluence.network to run the numbers for yourself.
☁ What if your cloud bill was actually affordable?
Most people just accept that running servers in the cloud is expensive. AWS charges you. DigitalOcean charges you. And you just, pay it, month after month, because what choice do you have?
Fluence just made that question a lot more interesting to answer.
Here is what the numbers actually look like for a 2 vCPU, 4 GB RAM, 25 GB Storage instance:
🔸AWS will take $69.50 from you every single month.
🔸DigitalOcean asks for $42.00.
🔸Hetzner brings it down to $17.60.
@Fluence ? Just $10.78.
That is not a rounding error. That is a 84% saving compared to AWS for the exact same instance specs. Even against Hetzner, widely known as one of the most budget friendly providers in the game, Fluence still comes out ahead.
What makes this even more compelling is the pricing calculator built right into their homepage. You pick your instance type, slide the additional storage and RAM controls to match your actual needs, and watch your real monthly cost update live.
For developers, startups, and indie builders who are tired of cloud bills eating their runway before their product even finds users, this is worth a serious look.
The decentralised compute era is here, and apparently it also comes with receipts.
Visit fluence.network to run the numbers for yourself.
Most people just accept that running servers in the cloud is expensive. AWS charges you. DigitalOcean charges you. And you just, pay it, month after month, because what choice do you have?
Fluence just made that question a lot more interesting to answer.
Here is what the numbers actually look like for a 2 vCPU, 4 GB RAM, 25 GB Storage instance:
🔸AWS will take $69.50 from you every single month.
🔸DigitalOcean asks for $42.00.
🔸Hetzner brings it down to $17.60.
@Fluence ? Just $10.78.
That is not a rounding error. That is a 84% saving compared to AWS for the exact same instance specs. Even against Hetzner, widely known as one of the most budget friendly providers in the game, Fluence still comes out ahead.
What makes this even more compelling is the pricing calculator built right into their homepage. You pick your instance type, slide the additional storage and RAM controls to match your actual needs, and watch your real monthly cost update live.
For developers, startups, and indie builders who are tired of cloud bills eating their runway before their product even finds users, this is worth a serious look.
The decentralised compute era is here, and apparently it also comes with receipts.
Visit fluence.network to run the numbers for yourself.
88
·
--
Why rent from one giant when you can tap the whole world?
The hyperscalers don't own the future of compute, the network does.
@fluence is building a decentralized GPU marketplace where teams launch, scale, and manage workloads across multiple providers without the lock in, markup, or single point of failure.
🔸Multi provider access in one layer
🔸0x Vendor lock-in
🔸Scale on demanding
Learn how it works👉 fluence.network
Why rent from one giant when you can tap the whole world?
The hyperscalers don't own the future of compute, the network does.
@Fluence is building a decentralized GPU marketplace where teams launch, scale, and manage workloads across multiple providers without the lock in, markup, or single point of failure.
🔸Multi provider access in one layer
🔸0x Vendor lock-in
🔸Scale on demanding
Learn how it works👉 fluence.network
The hyperscalers don't own the future of compute, the network does.
@Fluence is building a decentralized GPU marketplace where teams launch, scale, and manage workloads across multiple providers without the lock in, markup, or single point of failure.
🔸Multi provider access in one layer
🔸0x Vendor lock-in
🔸Scale on demanding
Learn how it works👉 fluence.network
171
·
--
Haussier
You're probably paying 3 to 6x more than you need to for cloud.
Most developers just spin up the nearest-familiar instance on AWS or DigitalOcean without a second thought and honestly? The cloud providers are counting on that.
The pricing page is a maze on purpose.
The pricing calculator from @fluence makes the gap embarrassingly visible. You tend to find out same specs and wildly different bills.
That's $694/year saved vs AWS. Just on a 2 vCPU, 4 GB RAM instance. If you scale that across a team running 10+ servers and you're looking at a real engineering salary sitting on the table.
The calculator lets you configure instance type, add storage, bump RAM and watch every competitor's price update in real time. No sign up, no sales call. Just the numbers, cold and clear.
This is the kind of tool that pays for itself in the first five minutes.
Wondering how to get started, visit the link below
👉 fluence.network
You're probably paying 3 to 6x more than you need to for cloud.
Most developers just spin up the nearest-familiar instance on AWS or DigitalOcean without a second thought and honestly? The cloud providers are counting on that.
The pricing page is a maze on purpose.
The pricing calculator from @Fluence makes the gap embarrassingly visible. You tend to find out same specs and wildly different bills.
That's $694/year saved vs AWS. Just on a 2 vCPU, 4 GB RAM instance. If you scale that across a team running 10+ servers and you're looking at a real engineering salary sitting on the table.
The calculator lets you configure instance type, add storage, bump RAM and watch every competitor's price update in real time. No sign up, no sales call. Just the numbers, cold and clear.
This is the kind of tool that pays for itself in the first five minutes.
Wondering how to get started, visit the link below
👉 fluence.network
Most developers just spin up the nearest-familiar instance on AWS or DigitalOcean without a second thought and honestly? The cloud providers are counting on that.
The pricing page is a maze on purpose.
The pricing calculator from @Fluence makes the gap embarrassingly visible. You tend to find out same specs and wildly different bills.
That's $694/year saved vs AWS. Just on a 2 vCPU, 4 GB RAM instance. If you scale that across a team running 10+ servers and you're looking at a real engineering salary sitting on the table.
The calculator lets you configure instance type, add storage, bump RAM and watch every competitor's price update in real time. No sign up, no sales call. Just the numbers, cold and clear.
This is the kind of tool that pays for itself in the first five minutes.
Wondering how to get started, visit the link below
👉 fluence.network
177
·
--
Haussier
Cloud bills shouldn’t be a guessing game.
@fluence Cloudless Virtual Servers flip the model: predictable daily pricing, the ability to set a max daily spend, and unlimited bandwidth with no egress fees.
No long-term lock-ins, no surprise charges, just enterprise-grade compute on decentralized infrastructure.
If you’re tired of traditional VPS pricing, this is what cloudless compute actually looks like.
👉 http://fluence.network
Cloud bills shouldn’t be a guessing game.
@Fluence Cloudless Virtual Servers flip the model: predictable daily pricing, the ability to set a max daily spend, and unlimited bandwidth with no egress fees.
No long-term lock-ins, no surprise charges, just enterprise-grade compute on decentralized infrastructure.
If you’re tired of traditional VPS pricing, this is what cloudless compute actually looks like.
👉 http://fluence.network
@Fluence Cloudless Virtual Servers flip the model: predictable daily pricing, the ability to set a max daily spend, and unlimited bandwidth with no egress fees.
No long-term lock-ins, no surprise charges, just enterprise-grade compute on decentralized infrastructure.
If you’re tired of traditional VPS pricing, this is what cloudless compute actually looks like.
👉 http://fluence.network
194
·
--
Baissier
Let's talk about the thing nobody in cloud computing wants you to know.
You're probably overpaying for your cloud infrastructure, and not by a little.
Hidden data transfer fees, storage markups, surprise bills at the end of the month.
Centralized cloud providers have built entire revenue models around your confusion.
@fluence is done with that.
🔹 Up to 75% cheaper than centralized cloud providers
🔹 Transparent, predictable pricing, no guesswork
🔹 Zero hidden fees for data transfer or storage
🔹 Pay ONLY for the compute you actually use
That's not a discount. That's a fundamentally better model.
When decentralization meets infrastructure, the only thing that changes is everything. ⚡
👉 fluence.network
Let's talk about the thing nobody in cloud computing wants you to know.
You're probably overpaying for your cloud infrastructure, and not by a little.
Hidden data transfer fees, storage markups, surprise bills at the end of the month.
Centralized cloud providers have built entire revenue models around your confusion.
@Fluence is done with that.
🔹 Up to 75% cheaper than centralized cloud providers
🔹 Transparent, predictable pricing, no guesswork
🔹 Zero hidden fees for data transfer or storage
🔹 Pay ONLY for the compute you actually use
That's not a discount. That's a fundamentally better model.
When decentralization meets infrastructure, the only thing that changes is everything. ⚡
👉 fluence.network
You're probably overpaying for your cloud infrastructure, and not by a little.
Hidden data transfer fees, storage markups, surprise bills at the end of the month.
Centralized cloud providers have built entire revenue models around your confusion.
@Fluence is done with that.
🔹 Up to 75% cheaper than centralized cloud providers
🔹 Transparent, predictable pricing, no guesswork
🔹 Zero hidden fees for data transfer or storage
🔹 Pay ONLY for the compute you actually use
That's not a discount. That's a fundamentally better model.
When decentralization meets infrastructure, the only thing that changes is everything. ⚡
👉 fluence.network
255
·
--
Your AI infra shouldn't be a hostage situation.
SageMaker, Azure ML, pretty packaging around a vendor trap.
Migration pain is by design, not accident.
The fix? Default to portability.
Deploy on @fluence Virtual Servers using standard Docker containers & infrastructure as code. No proprietary lock-in, No switching penalties.
Just open protocols that let you pack up your stack and move, whenever, wherever.
Decentralized infra isn't just ideological. It's strategic.
👉 fluence.network/virtual-servers
Your AI infra shouldn't be a hostage situation.
SageMaker, Azure ML, pretty packaging around a vendor trap.
Migration pain is by design, not accident.
The fix? Default to portability.
Deploy on @Fluence Virtual Servers using standard Docker containers & infrastructure as code. No proprietary lock-in, No switching penalties.
Just open protocols that let you pack up your stack and move, whenever, wherever.
Decentralized infra isn't just ideological. It's strategic.
👉 fluence.network/virtual-servers
SageMaker, Azure ML, pretty packaging around a vendor trap.
Migration pain is by design, not accident.
The fix? Default to portability.
Deploy on @Fluence Virtual Servers using standard Docker containers & infrastructure as code. No proprietary lock-in, No switching penalties.
Just open protocols that let you pack up your stack and move, whenever, wherever.
Decentralized infra isn't just ideological. It's strategic.
👉 fluence.network/virtual-servers
176
·
--
Haussier
The future of the internet won’t rely on a handful of cloud providers controlling the infrastructure.
With @fluence , compute becomes decentralized, verifiable, and open to everyone.
By using unused capacity from data centers around the world, Fluence creates a global marketplace for computing power.
The result?
⚡ Up to 80% cheaper compute
🔐 Cryptographically verifiable execution
🌍 A censorship-resistant network
Welcome to the era of Cloudless Computing.
👉 http://fluence.network
The future of the internet won’t rely on a handful of cloud providers controlling the infrastructure.
With @Fluence , compute becomes decentralized, verifiable, and open to everyone.
By using unused capacity from data centers around the world, Fluence creates a global marketplace for computing power.
The result?
⚡ Up to 80% cheaper compute
🔐 Cryptographically verifiable execution
🌍 A censorship-resistant network
Welcome to the era of Cloudless Computing.
👉 http://fluence.network
With @Fluence , compute becomes decentralized, verifiable, and open to everyone.
By using unused capacity from data centers around the world, Fluence creates a global marketplace for computing power.
The result?
⚡ Up to 80% cheaper compute
🔐 Cryptographically verifiable execution
🌍 A censorship-resistant network
Welcome to the era of Cloudless Computing.
👉 http://fluence.network
171
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--
Haussier
Decentralization isn’t complete without compute.
We’ve solved money (Bitcoin) and storage ( Filecoin), but the actual processing power behind apps is still locked in centralized clouds.
@fluence unlocks that layer by creating a global, decentralized compute marketplace powered by real data centers.
Lower costs, verifiable execution, and no single point of control. That’s what Cloudless Computing brings to the table.
Decentralization isn’t complete without compute.
We’ve solved money (Bitcoin) and storage ( Filecoin), but the actual processing power behind apps is still locked in centralized clouds.
@Fluence unlocks that layer by creating a global, decentralized compute marketplace powered by real data centers.
Lower costs, verifiable execution, and no single point of control. That’s what Cloudless Computing brings to the table.
We’ve solved money (Bitcoin) and storage ( Filecoin), but the actual processing power behind apps is still locked in centralized clouds.
@Fluence unlocks that layer by creating a global, decentralized compute marketplace powered by real data centers.
Lower costs, verifiable execution, and no single point of control. That’s what Cloudless Computing brings to the table.
338
·
--
Haussier
Cloudless on your terms isn’t just a tagline, it’s the future of infrastructure. ⚡
With @fluence , developers get predictable billing, zero lock-ins, and the freedom to deploy GPU workloads anywhere with ease. From AI training to scalable compute, Fluence puts control back into the hands of builders.
No hidden costs, no restrictions. Just fast, flexible, decentralized compute. 🌐🔥
The cloud era was centralized.
The next era is Cloudless.
Cloudless on your terms isn’t just a tagline, it’s the future of infrastructure. ⚡
With @Fluence , developers get predictable billing, zero lock-ins, and the freedom to deploy GPU workloads anywhere with ease. From AI training to scalable compute, Fluence puts control back into the hands of builders.
No hidden costs, no restrictions. Just fast, flexible, decentralized compute. 🌐🔥
The cloud era was centralized.
The next era is Cloudless.
With @Fluence , developers get predictable billing, zero lock-ins, and the freedom to deploy GPU workloads anywhere with ease. From AI training to scalable compute, Fluence puts control back into the hands of builders.
No hidden costs, no restrictions. Just fast, flexible, decentralized compute. 🌐🔥
The cloud era was centralized.
The next era is Cloudless.
345
·
--
People still ask, “What can actually run on @fluence ?”
Maybe the better question is: “What CAN’T?”
AI workloads, web hosting, API services, blockchain nodes, validator, data analytics, rendering.
From CPU-heavy tasks to GPU-powered workloads, Fluence gives builders the freedom to deploy across multiple regions without being boxed into a single cloud provider.
The future of cloud infrastructure isn’t just decentralized.
It’s flexible, scalable, and built for everything the internet is becoming.
People still ask, “What can actually run on @Fluence ?”
Maybe the better question is: “What CAN’T?”
AI workloads, web hosting, API services, blockchain nodes, validator, data analytics, rendering.
From CPU-heavy tasks to GPU-powered workloads, Fluence gives builders the freedom to deploy across multiple regions without being boxed into a single cloud provider.
The future of cloud infrastructure isn’t just decentralized.
It’s flexible, scalable, and built for everything the internet is becoming.
Maybe the better question is: “What CAN’T?”
AI workloads, web hosting, API services, blockchain nodes, validator, data analytics, rendering.
From CPU-heavy tasks to GPU-powered workloads, Fluence gives builders the freedom to deploy across multiple regions without being boxed into a single cloud provider.
The future of cloud infrastructure isn’t just decentralized.
It’s flexible, scalable, and built for everything the internet is becoming.
268
·
--
Haussier
Think about the possibilities when compute becomes transparent and verifiable.
AI models could prove which datasets were used.
Biotech researchers could analyze sensitive data without relying on centralized infrastructure.
Climate scientists could process massive datasets with full transparency.
This is the power of @fluence 's Cloudless Computing, a decentralized network designed to bring openness, security, and efficiency back to the internet’s core infrastructure. 🚀
👉 fluence.network
Think about the possibilities when compute becomes transparent and verifiable.
AI models could prove which datasets were used.
Biotech researchers could analyze sensitive data without relying on centralized infrastructure.
Climate scientists could process massive datasets with full transparency.
This is the power of @Fluence 's Cloudless Computing, a decentralized network designed to bring openness, security, and efficiency back to the internet’s core infrastructure. 🚀
👉 fluence.network
AI models could prove which datasets were used.
Biotech researchers could analyze sensitive data without relying on centralized infrastructure.
Climate scientists could process massive datasets with full transparency.
This is the power of @Fluence 's Cloudless Computing, a decentralized network designed to bring openness, security, and efficiency back to the internet’s core infrastructure. 🚀
👉 fluence.network
1
162
·
--
Haussier
Sometimes the hardest part of building AI infrastructure isn’t the model, it’s choosing the right hardware to run it.
That’s something I like about what @fluence is doing here. Instead of leaving developers guessing which GPU fits their workload, they’ve made it easier to match use cases with the right compute power.
Instead of stitching together multiple compute solutions, the idea is simple: choose the workload, pick the GPU, and deploy.
For anyone building AI agents, training models, or running inference pipelines, having this level of clarity around compute options can save a lot of trial and error.
Sometimes better infrastructure isn’t about adding more tools, it’s about making the right ones easier to use.🚀
👉http://fluence.network
Sometimes the hardest part of building AI infrastructure isn’t the model, it’s choosing the right hardware to run it.
That’s something I like about what @Fluence is doing here. Instead of leaving developers guessing which GPU fits their workload, they’ve made it easier to match use cases with the right compute power.
Instead of stitching together multiple compute solutions, the idea is simple: choose the workload, pick the GPU, and deploy.
For anyone building AI agents, training models, or running inference pipelines, having this level of clarity around compute options can save a lot of trial and error.
Sometimes better infrastructure isn’t about adding more tools, it’s about making the right ones easier to use.🚀
👉http://fluence.network
That’s something I like about what @Fluence is doing here. Instead of leaving developers guessing which GPU fits their workload, they’ve made it easier to match use cases with the right compute power.
Instead of stitching together multiple compute solutions, the idea is simple: choose the workload, pick the GPU, and deploy.
For anyone building AI agents, training models, or running inference pipelines, having this level of clarity around compute options can save a lot of trial and error.
Sometimes better infrastructure isn’t about adding more tools, it’s about making the right ones easier to use.🚀
👉http://fluence.network
150
·
--
Haussier
You know you're overpaying for cloud. You just don't know how much.
I ran the numbers on a standard 2 vCPU, 4 GB RAM setup:
AWS: $69.50/month
DigitalOcean: $42.00/month
Hetzner: $17.60/month
Fluence: $10.78/month
That’s not a typo. Same specs, same workload. Just without the cloud tax.
@fluence isn't asking you to sacrifice performance for price. It's DePIN-powered, enterprise-grade compute with unlimited bandwidth.
No hidden egress fees, no surprise bills.
The real question isn't "is Fluence secure enough?"
It's "why are you still paying 6x more?"
Try their cost calculator, you might sleep better this weekend.
You know you're overpaying for cloud. You just don't know how much.
I ran the numbers on a standard 2 vCPU, 4 GB RAM setup:
AWS: $69.50/month
DigitalOcean: $42.00/month
Hetzner: $17.60/month
Fluence: $10.78/month
That’s not a typo. Same specs, same workload. Just without the cloud tax.
@Fluence isn't asking you to sacrifice performance for price. It's DePIN-powered, enterprise-grade compute with unlimited bandwidth.
No hidden egress fees, no surprise bills.
The real question isn't "is Fluence secure enough?"
It's "why are you still paying 6x more?"
Try their cost calculator, you might sleep better this weekend.
I ran the numbers on a standard 2 vCPU, 4 GB RAM setup:
AWS: $69.50/month
DigitalOcean: $42.00/month
Hetzner: $17.60/month
Fluence: $10.78/month
That’s not a typo. Same specs, same workload. Just without the cloud tax.
@Fluence isn't asking you to sacrifice performance for price. It's DePIN-powered, enterprise-grade compute with unlimited bandwidth.
No hidden egress fees, no surprise bills.
The real question isn't "is Fluence secure enough?"
It's "why are you still paying 6x more?"
Try their cost calculator, you might sleep better this weekend.
100
·
--
Haussier
The wait is over. @fluence has just taken the wraps off a brand-new website, and this time, GPU access isn’t locked behind gates, it’s fully open to new users.
Here’s what’s real, starting today, you can spin up GPU Containers, Virtual Machines, and Bare Metal deployments instantly via the Fluence Console.
No enterprise runaround, no hidden approvals.
🌎 The scale is impressive, 1,400+ GPUs spread across 32 regions and 71 data centers worldwide.
Getting started takes three steps:
✅Sign up with GitHub, Google, or Email
✅Top up your balance
✅Deploy your first workload
This isn’t a teaser, it’s live. If you need serious compute, the only question left is: what will you build first?
👉 https://console.fluence.network/auth/sign-up
The wait is over. @Fluence has just taken the wraps off a brand-new website, and this time, GPU access isn’t locked behind gates, it’s fully open to new users.
Here’s what’s real, starting today, you can spin up GPU Containers, Virtual Machines, and Bare Metal deployments instantly via the Fluence Console.
No enterprise runaround, no hidden approvals.
🌎 The scale is impressive, 1,400+ GPUs spread across 32 regions and 71 data centers worldwide.
Getting started takes three steps:
✅Sign up with GitHub, Google, or Email
✅Top up your balance
✅Deploy your first workload
This isn’t a teaser, it’s live. If you need serious compute, the only question left is: what will you build first?
👉 https://console.fluence.network/auth/sign-up
Here’s what’s real, starting today, you can spin up GPU Containers, Virtual Machines, and Bare Metal deployments instantly via the Fluence Console.
No enterprise runaround, no hidden approvals.
🌎 The scale is impressive, 1,400+ GPUs spread across 32 regions and 71 data centers worldwide.
Getting started takes three steps:
✅Sign up with GitHub, Google, or Email
✅Top up your balance
✅Deploy your first workload
This isn’t a teaser, it’s live. If you need serious compute, the only question left is: what will you build first?
👉 https://console.fluence.network/auth/sign-up
1
73
·
--
Unbundling the Internet: Why the "Cloudless" Future is More Than Just a MemeIf you’ve been watching the DePIN and Decentralized Compute space lately, you’ve probably noticed that we’re moving away from "all-in-one" blockchains toward a modular stack where every resource (bandwidth, connectivity, information, and compute) is its own marketplace.
Comparing Orchid ($OXT), Roam ($ROAM), Augur ($REP), and Fluence ($FLT) reveals a fascinating arc of Web3 infrastructure.
Here is what stands out from the digital trenches:
🧱 Four Pillars, Four Resources
While all these projects fall under "infrastructure," they are solving fundamentally different bottlenecks:
Bandwidth & Privacy ($OXT): Orchid pioneered the market for VPN bandwidth, trying to turn privacy into a stakable resource.
Connectivity & Wireless ($ROAM): A newer DePIN player focused on "crypto telco" services, specifically bringing wireless access to the Solana and BNB ecosystems.
Information & Intelligence ($REP): An OG prediction market protocol that functions as a decentralized oracle network for collective forecasting.
The Execution Engine ($FLT): Fluence sits at the top of this stack as a serverless compute protocol.
🧠 Why Fluence is the Glue for AI Infrastructure
While the older projects like Orchid and Augur laid the groundwork for resource marketplaces, Fluence feels like the missing piece for the current AI and Agentic narrative.
In 2026, Fluence has realized that owning the hardware (GPUs) isn’t enough. We need a way to orchestrate logic across a peer network without a central cloud provider acting as a chokepoint.
How Fluence fits the bigger picture:
The Runtime over the Metal: Unlike projects that just rent you a virtual machine, Fluence is a programmable compute fabric. It’s where developers actually deploy the code that runs the AI agents.
Modular Synergy: Imagine an AI agent that pulls prediction data from Augur, routes its communication through Orchid for privacy, and executes its logic on Fluence. That is a truly resilient, unbundled application.
The Cloudless Mission: Fluence’s goal isn’t just to be another compute coin. It’s to provide a verifiable alternative to the Big Tech cloud monopoly, ensuring that the logic of our future apps isn't owned by a single company.
🎯 The Bottom Line
Many of these legacy infrastructure tokens have seen 90–99% drawdowns, serving as a grounded reminder that narrative fit is not the same as adoption. While Fluence is the youngest and smallest in market cap, it is positioning itself as the glue layer. It doesn't just provide a resource; it provides the execution that turns raw bandwidth, data, and connectivity into functional, decentralized applications.
Summary: We are moving from buying a machine to calling a service. If the future of Web3 is truly cloudless, the coordination layer where $FLT sits will be the most critical piece of the puzzle.
Unbundling the Internet: Why the "Cloudless" Future is More Than Just a Meme
If you’ve been watching the DePIN and Decentralized Compute space lately, you’ve probably noticed that we’re moving away from "all-in-one" blockchains toward a modular stack where every resource (bandwidth, connectivity, information, and compute) is its own marketplace.
Comparing Orchid ($OXT), Roam ($ROAM), Augur ($REP), and Fluence ($FLT) reveals a fascinating arc of Web3 infrastructure.
Here is what stands out from the digital trenches:
🧱 Four Pillars, Four Resources
While all these projects fall under "infrastructure," they are solving fundamentally different bottlenecks:
Bandwidth & Privacy ($OXT): Orchid pioneered the market for VPN bandwidth, trying to turn privacy into a stakable resource.
Connectivity & Wireless ($ROAM): A newer DePIN player focused on "crypto telco" services, specifically bringing wireless access to the Solana and BNB ecosystems.
Information & Intelligence ($REP): An OG prediction market protocol that functions as a decentralized oracle network for collective forecasting.
The Execution Engine ($FLT): Fluence sits at the top of this stack as a serverless compute protocol.
🧠 Why Fluence is the Glue for AI Infrastructure
While the older projects like Orchid and Augur laid the groundwork for resource marketplaces, Fluence feels like the missing piece for the current AI and Agentic narrative.
In 2026, Fluence has realized that owning the hardware (GPUs) isn’t enough. We need a way to orchestrate logic across a peer network without a central cloud provider acting as a chokepoint.
How Fluence fits the bigger picture:
The Runtime over the Metal: Unlike projects that just rent you a virtual machine, Fluence is a programmable compute fabric. It’s where developers actually deploy the code that runs the AI agents.
Modular Synergy: Imagine an AI agent that pulls prediction data from Augur, routes its communication through Orchid for privacy, and executes its logic on Fluence. That is a truly resilient, unbundled application.
The Cloudless Mission: Fluence’s goal isn’t just to be another compute coin. It’s to provide a verifiable alternative to the Big Tech cloud monopoly, ensuring that the logic of our future apps isn't owned by a single company.
🎯 The Bottom Line
Many of these legacy infrastructure tokens have seen 90–99% drawdowns, serving as a grounded reminder that narrative fit is not the same as adoption. While Fluence is the youngest and smallest in market cap, it is positioning itself as the glue layer. It doesn't just provide a resource; it provides the execution that turns raw bandwidth, data, and connectivity into functional, decentralized applications.
Summary: We are moving from buying a machine to calling a service. If the future of Web3 is truly cloudless, the coordination layer where $FLT sits will be the most critical piece of the puzzle.
Comparing Orchid ($OXT), Roam ($ROAM), Augur ($REP), and Fluence ($FLT) reveals a fascinating arc of Web3 infrastructure.
Here is what stands out from the digital trenches:
🧱 Four Pillars, Four Resources
While all these projects fall under "infrastructure," they are solving fundamentally different bottlenecks:
Bandwidth & Privacy ($OXT): Orchid pioneered the market for VPN bandwidth, trying to turn privacy into a stakable resource.
Connectivity & Wireless ($ROAM): A newer DePIN player focused on "crypto telco" services, specifically bringing wireless access to the Solana and BNB ecosystems.
Information & Intelligence ($REP): An OG prediction market protocol that functions as a decentralized oracle network for collective forecasting.
The Execution Engine ($FLT): Fluence sits at the top of this stack as a serverless compute protocol.
🧠 Why Fluence is the Glue for AI Infrastructure
While the older projects like Orchid and Augur laid the groundwork for resource marketplaces, Fluence feels like the missing piece for the current AI and Agentic narrative.
In 2026, Fluence has realized that owning the hardware (GPUs) isn’t enough. We need a way to orchestrate logic across a peer network without a central cloud provider acting as a chokepoint.
How Fluence fits the bigger picture:
The Runtime over the Metal: Unlike projects that just rent you a virtual machine, Fluence is a programmable compute fabric. It’s where developers actually deploy the code that runs the AI agents.
Modular Synergy: Imagine an AI agent that pulls prediction data from Augur, routes its communication through Orchid for privacy, and executes its logic on Fluence. That is a truly resilient, unbundled application.
The Cloudless Mission: Fluence’s goal isn’t just to be another compute coin. It’s to provide a verifiable alternative to the Big Tech cloud monopoly, ensuring that the logic of our future apps isn't owned by a single company.
🎯 The Bottom Line
Many of these legacy infrastructure tokens have seen 90–99% drawdowns, serving as a grounded reminder that narrative fit is not the same as adoption. While Fluence is the youngest and smallest in market cap, it is positioning itself as the glue layer. It doesn't just provide a resource; it provides the execution that turns raw bandwidth, data, and connectivity into functional, decentralized applications.
Summary: We are moving from buying a machine to calling a service. If the future of Web3 is truly cloudless, the coordination layer where $FLT sits will be the most critical piece of the puzzle.
1
394
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