For GPU cloud operators looking to move beyond GPU rentals and offer a more complete offering, Saturn Cloud and Rafay integrate sellable AI services so you don't have to build the stack yourself. Rafay orchestrates infrastructure and multi-tenancy, while Saturn Cloud adds managed environments, fine-tuning, serving, and per-token inference. Learn more here: lnkd.in/gbM_y8QZ #SaturnCloud #Rafay #AICloud #GPUCloud #Neocloud

Telcos already have GPUs, data centers within national borders, and regulated customers who need compliant AI. But how do they charge for it? Renting GPUs by the hour caps revenue, but billing per token doesn't, because the same GPU can serve more tokens. NVIDIA's own analysis of telco AI factories pegs that at around 8x the annual revenue of hourly rental on the same hardware. Telcos spent a decade building the infrastructure, and this is how they make money on the AI running on top of it: saturncloud.io/blog/how-telc… #SovereignAI #Telco #AIInfrastructure #TokenFactory #GPUCloud

We broke down the cost of maintaining a model catalog and where Saturn Cloud comes in. Every time new models, hardware, or engine updates land, we turn them into supported, pre-tuned configurations across your existing fleet, so your catalog stays current and your GPUs stay earning, without a team tracking every driver, kernel, and model drop. Learn more: saturncloud.io/blog/the-cost… #GPUCloud #AIInfrastructure #Inference #TokenFactory

Enterprise customers want their own isolated environment. For a GPU cloud, that usually means building one by hand, again, for every new customer. That’s the part we got rid of. Saturn Cloud is now a vCluster Stack, built with @vcluster. That means an operator sets up the environment once. After that, each new customer gets their own isolated cluster on the operator’s GPUs, with Saturn Cloud inside it and per-token endpoints ready to call. The second customer takes the same steps as the first. So does the fiftieth. We wrote up how it works, including what onboarding a customer looks like. Link below. #vCluster #GPUCloud #AIInfrastructure #Inference #Kubernetes

We will be at GTC Berlin this week, see you there! Saturn Cloud is helping AI Clouds improve GPU utilization and deliver scalable, multi-tenant AI services. From inference and fine-tuning to dedicated capacity, providers can offer more services from the same infrastructure Come find us if you're building on GPU infrastructure and want to learn how it works. #NVIDIA #NVIDIAGTC #GPUCloud #AICloud #Neocloud #TokenFactory

With @NVIDIAAI Run:ai + Saturn Cloud, operators get NVIDIA’s orchestration layer and Saturn Cloud’s commercial layer, combining them to turn raw GPU capacity into per-token inference products they can sell. Omri Geller, VP at NVIDIA, shares what the integration gives GPU cloud operators. Read more here: saturncloud.io/blog/turn-a-g… #SaturnCloud #NVIDIA #AICloud #Inference

📢 Saturn Cloud is now a @vcluster Stack. We’re excited to partner with @vclusterlabs to help AI clouds sell managed, per-token inference on their own GPUs. With Stacks, operators define an environment once and deploy it the same way for every customer. Each customer gets their own tenant cluster on vCluster Private Nodes, with isolated network, storage, and compute. The operator deploys the Saturn Cloud Stack into it, and the customer can start calling per-token endpoints. Beyond inference, Saturn Cloud also runs dedicated GPU capacity, managed fine-tuning, and distributed training on the same fleet. The first version of the Saturn Cloud Stack is available today. Thank you to the vCluster team for working with us on this. Read the full announcement here: lnkd.in/gPt8jvmK Learn more about Stacks in vCluster Platform 4.12: lnkd.in/gkRMaiqi #AIInfrastructure #Inference #vCluster #GPUCloud

We’re excited to announce that Saturn Cloud now integrates the full open-source @NVIDIAAI Run:ai platform, deployed on an operator’s own cluster. NVIDIA has open sourced NVIDIA Run:ai as part of the NVIDIA DSX AI Factory Platform, so AI cloud operators can run it without a paid NVIDIA Run:ai subscription. Saturn Cloud combines NVIDIA Run:ai, KAI Scheduler, and NVIDIA Dynamo into one platform that takes operators from GPU fleet to branded AI services. Operators can sell the same fleet as dedicated GPU capacity, per-token model-as-a-service, or managed fine-tuning, all billed through one system. Neoclouds, telcos, and enterprise AI factory operators can now deploy and run NVIDIA Run:ai as part of a complete platform. Thanks to the NVIDIA Run:ai team for their collaboration on this integration. 🔹 Read about the integration here: lnkd.in/gnfBQYP8 🔹 Learn more about NVIDIA Run:ai here: lnkd.in/eps4hY6M #OpenSource #AIInfrastructure #AICloud #NVIDIADSX #NVIDIARunAI #NVIDIA

If you run a GPU cloud, the platform layer is either months of your engineers' time or something you buy. We laid out what building it in-house actually takes, what it costs, and where the math tips toward buying. A production build can run close to a year, plus a couple of engineers on maintenance indefinitely. Instead, deploying something like Saturn Cloud takes weeks, white-labeled on your own infrastructure. The post also covers the cases where building still makes sense. Read more here: lnkd.in/gU7eekPY #AICloud #GPUCloud #SaturnCloud

If you're scaling LLM training beyond a single node, interconnect matters. Learn how to provision a 2-node A100 cluster on Crusoe with InfiniBand using Terraform, with working config and distributed training setup included: lnkd.in/gBxPvBda #Crusoe #GPUs #Terraform #LLM #SaturnCloud

We rented a GPU VM from Shadeform, joined it to a k0smotron-hosted control plane, and ran real workloads on it. Our breakdown covers two cross-node networking problems that showed up when nodes lived in different clouds, and how we worked around them. If you're stitching GPUs from more than one provider into one Kubernetes cluster, cross-node networking is where the time actually goes. Learn more here: lnkd.in/gebueAnU #DevOps #GPUComputing #k0smotron

Together, Saturn Cloud + @MirantisIT k0rdent, give GPU providers a complete AI platform to offer their customers, with k0rdent handling infrastructure management and Saturn Cloud handling the application layer, without building either from scratch. Learn more here: lnkd.in/gxZm_4FC #Mirantis #GPUs #AI #SaturnCloud #AICloud #GPUCloud

AI clouds can now get more from every GPU. Together with @NVIDIAAI Run:ai, Saturn Cloud is helping AI Clouds improve GPU utilization and deliver scalable, multi-tenant AI services. From inference and fine-tuning to dedicated capacity, providers can offer more services from the same infrastructure. Learn more here: saturncloud.io/blog/turn-a-g… #NVIDIA #AICloud #GPUCloud #Inference

Thank you to everyone who joined us and @MirantisIT last night for our executive dinner for neocloud and AI service providers in Manhattan. Great conversations and even better company. More evenings like this to come - stay tuned.

We mapped the open-source AI stack by category, control model, and the trade-offs that separate projects within each one, so you can add any new tool the day it launches instead of relearning a list. We're covering agent orchestration, MCP and A2A, RAG and vector DBs, gateways vs. inference routers, serving engines, distributed training, fine-tuning, and RL post-training. Two things we were careful about were flagging which projects are neutral-governance vs. single-vendor open-core, and skipping the benchmark numbers that are really just each project's own marketing. More here: lnkd.in/g-6PMkjE #AIEngineering #OpenSource #LLMs #AIFrameworks #MLOps #FineTuning

We will be at Yotta this week, see you there! Saturn Cloud turns GPU infrastructure into a token factory. We give AI cloud operators, neoclouds, and telcos a platform layer for managed fine-tuning, model serving, and per-token inference, so they can sell AI services instead of GPU hours. Come find us if you're building on GPU infrastructure and want to learn how it works. #AIInfraSummit #GPUCloud #AICloud #Neocloud #TokenFactory

Saturn Cloud gives AI cloud operators everything they need to turn a GPU fleet into products their tenants can buy. They can sell dedicated capacity by the hour, per-token model-as-a-service, and self-service environments for teams building and fine-tuning their own models. Tenants get a production AI workflow on day one. Operators get a business to sell, with no internal platform build and no months of engineering. Available for AI clouds here: saturncloud.io #AIInfrastructure #GPUCloud #Neocloud #AIFactory #MLOps

We broke down the real cost of maintaining a model catalog and where Saturn Cloud comes in. Every time new models, hardware, or engine updates land, we turn them into supported, pre-tuned configurations across your existing fleet, so your catalog stays current and your GPUs stay earning, without a team tracking every driver, kernel, and model drop. Learn more here: lnkd.in/g3X9x_yD #GPUCloud #AIInfrastructure #Inference #TokenFactory

Learn how to set up @NVIDIAAI NIM on Saturn Cloud. NVIDIA NIM turns model deployment into a single container pull. You get the model, an optimized TensorRT-LLM backend, and a standard inference API in one image. NVIDIA's benchmark puts it at roughly 2x the throughput of a standard FP8 deployment on the same H100, with no manual tuning. Our guide runs the full setup on a Saturn Cloud H100, from pull to first request, plus LoRA serving and multi-GPU scaling. Read it here: lnkd.in/gCfipAAA #NVIDIA #NVIDIANIM #LLM

Telcos already have GPUs, data centers within national borders, and regulated customers who need compliant AI. But how do they charge for it? Renting GPUs by the hour caps revenue, but billing per token doesn't, because the same GPU serves more tokens you can bill for. NVIDIA's own analysis of telco AI factories pegs that at around 8x the annual revenue of hourly rental on the same hardware. Telcos spent a decade building the infrastructure, and this is how they make money on the AI running on top of it: saturncloud.io/blog/how-telc… #SovereignAI #Telco #AIInfrastructure #TokenFactory #GPUCloud