Banana Alternatives

Build, deploy, and scale machine learning (ML) models faster, with fully managed ML tools for any use case. Through Vertex AI Workbench, Vertex AI is natively integrated with BigQuery, Dataproc, and Spark. You can use BigQuery ML to create and execute machine learning models in BigQuery using standard SQL queries on existing business intelligence tools and spreadsheets, or you can export datasets from BigQuery directly into Vertex AI Workbench and run your models from there. Use Vertex Data Labeling to generate highly accurate labels for your data collection.

Everything that you need to deploy and manage single-tenant, high-performance bare metal servers. If you are used to VMs, Latitude.sh will make you feel right at home — but with a lot more computing power. Get the speed of a dedicated physical server and the flexibility of the cloud—deploy instantly and manage your servers through the Control Panel or our powerful API. Hardware and connectivity solutions specific to your needs, while you still benefit from all the automation Latitude.sh is built on. Power your team with a robust, easy-to-use control panel, which you can use to view and change your infrastructure in real time. If you're like most of our customers, you're looking at Latitude.sh to run mission-critical services where uptime and latency are extremely important. We built our own private data center, so we know what great infrastructure looks like.

Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. SageMaker removes the heavy lifting from each step of the machine learning process to make it easier to develop high quality models. Traditional ML development is a complex, expensive, iterative process made even harder because there are no integrated tools for the entire machine learning workflow. You need to stitch together tools and workflows, which is time-consuming and error-prone. SageMaker solves this challenge by providing all of the components used for machine learning in a single toolset so models get to production faster with much less effort and at lower cost. Amazon SageMaker Studio provides a single, web-based visual interface where you can perform all ML development steps. SageMaker Studio gives you complete access, control, and visibility into each step required.

Easily deploy cloud servers, bare metal, and storage worldwide! Our high performance compute instances are perfect for your web application or development environment. As soon as you click deploy, the Vultr cloud orchestration takes over and spins up your instance in your desired data center. Spin up a new instance with your preferred operating system or pre-installed application in just seconds. Enhance the capabilities of your cloud servers on demand. Automatic backups are extremely important for mission critical systems. Enable scheduled backups with just a few clicks from the customer portal. Our easy-to-use control panel and API let you spend more time coding and less time managing your infrastructure.

The NVIDIA GPU-Optimized AMI is a virtual machine image for accelerating your GPU accelerated Machine Learning, Deep Learning, Data Science and HPC workloads. Using this AMI, you can spin up a GPU-accelerated EC2 VM instance in minutes with a pre-installed Ubuntu OS, GPU driver, Docker and NVIDIA container toolkit. This AMI provides easy access to NVIDIA's NGC Catalog, a hub for GPU-optimized software, for pulling & running performance-tuned, tested, and NVIDIA certified docker containers. The NGC catalog provides free access to containerized AI, Data Science, and HPC applications, pre-trained models, AI SDKs and other resources to enable data scientists, developers, and researchers to focus on building and deploying solutions. This GPU-optimized AMI is free with an option to purchase enterprise support offered through NVIDIA AI Enterprise. For how to get support for this AMI, scroll down to 'Support Information'

Our infrastructure is equipped to meet your computing requirements, be it one or thousands of GPUs, or one vCPU to tens of thousands of vCPUs, we've got you covered. Our resources are readily available to cater to your needs, whenever you need them. Switching between GPU and CPU instances is a breeze with our platform. You have the flexibility to deploy, modify, and rescale your instances according to your needs, without any hassle. Outstanding machine learning performance without breaking the bank. The latest technology at a significantly lower cost. Cutting-edge GPUs are designed to meet the demands of your workloads. Gain access to computational resources that are tailored to suit the intricacies of your models. Leverage our infrastructure to perform large-scale inference and access necessary libraries with our OblivusAI OS. Unleash the full potential of your gaming experience by utilizing our robust infrastructure to play games in the settings of your choice.

Train the most demanding AI, ML, and Deep Learning models. Scale from a single machine to an entire fleet of VMs with a few clicks. Start or scale up your Deep Learning project with Lambda Cloud. Get started quickly, save on compute costs, and easily scale to hundreds of GPUs. Every VM comes preinstalled with the latest version of Lambda Stack, which includes major deep learning frameworks and CUDA® drivers. In seconds, access a dedicated Jupyter Notebook development environment for each machine directly from the cloud dashboard. For direct access, connect via the Web Terminal in the dashboard or use SSH directly with one of your provided SSH keys. By building compute infrastructure at scale for the unique requirements of deep learning researchers, Lambda can pass on significant savings. Benefit from the flexibility of using cloud computing without paying a fortune in on-demand pricing when workloads rapidly increase.

We have set up all the infrastructure, computing, and software (Cuda, Frameworks) required for you to train and deploy your favorite deep-learning models. You can spin up GPU/CPU-powered instances directly from your browser or automate it through our Python API.

Hyperstack is the ultimate self-service, on-demand GPUaaS Platform offering the H100, A100, L40 and more, delivering its services to some of the most promising AI start-ups in the world. Hyperstack is built for enterprise-grade GPU-acceleration and optimised for AI workloads, offering NexGen Cloud’s enterprise-grade infrastructure to a wide spectrum of users, from SMEs to Blue-Chip corporations, Managed Service Providers, and tech enthusiasts. Running on 100% renewable energy and powered by NVIDIA architecture, Hyperstack offers its services at up to 75% more cost-effective than Legacy Cloud Providers. The platform supports a diverse range of high-intensity workloads, such as Generative AI, Large Language Modelling, machine learning, and rendering.

Find, provision, and configure AI-ready cloud instances for dev, training, and deployment. Automatically install CUDA and Python, load the model, and SSH in. Use Brev.dev to find a GPU and get it configured to fine-tune or train your model. A single interface between AWS, GCP, and Lambda GPU cloud. Use credits when you have them. Pick an instance based on costs & availability. A CLI to automatically update your SSH config ensuring it's done securely. Build faster with a better dev environment. Brev connects to cloud providers to find you a GPU at the best price, configures it, and wraps SSH to connect your code editor to the remote machine. Change your instance, add or remove a GPU, add GB to your hard drive, etc. Set up your environment to make sure your code always runs, and make it easy to share or clone. You can create your own instance from scratch or use a template. The console should give you a couple of template options.

Speed up compute jobs like machine learning and HPC. A wide selection of GPUs to match a range of performance and price points. Flexible pricing and machine customizations to optimize your workload. High-performance GPUs on Google Cloud for machine learning, scientific computing, and 3D visualization. NVIDIA K80, P100, P4, T4, V100, and A100 GPUs provide a range of compute options to cover your workload for each cost and performance need. Optimally balance the processor, memory, high-performance disk, and up to 8 GPUs per instance for your individual workload. All with the per-second billing, so you only pay only for what you need while you are using it. Run GPU workloads on Google Cloud Platform where you have access to industry-leading storage, networking, and data analytics technologies. Compute Engine provides GPUs that you can add to your virtual machine instances. Learn what you can do with GPUs and what types of GPU hardware are available.

The first integrated hardware and software compute protocol to train and fine-tune your AI models. Lower your training costs by up to 80%. Deploy in seconds with open-source model templates or bring your own model. Seamlessly debug containers with access to GPU, CPU, Memory, and other metrics. You can monitor logs in real time. Trace all models and training sets with cryptographic verified proofs for complete accountability. Control the entire training workflow with a few simple commands. Earn block rewards for adding your computer to the network. Track key metrics such as connectivity and uptime.

Traditionally, deep learning, 3D modeling, simulations, distributed analytics, and molecular modeling take days or weeks time. However, with GPUonCLOUD’s dedicated GPU servers, it's a matter of hours. You may want to opt for pre-configured systems or pre-built instances with GPUs featuring deep learning frameworks like TensorFlow, PyTorch, MXNet, TensorRT, libraries e.g. real-time computer vision library OpenCV, thereby accelerating your AI/ML model-building experience. Among the wide variety of GPUs available to us, some of the GPU servers are best fit for graphics workstations and multi-player accelerated gaming. Instant jumpstart frameworks increase the speed and agility of the AI/ML environment with effective and efficient environment lifecycle management.

Unlock 3-5x better prices than traditional clouds. FluidStack aggregates under-utilized GPUs from data centers around the world to deliver the industry’s best economics. Deploy 50,000+ high-performance servers in seconds via a single platform and API. Access large-scale A100 and H100 clusters with InfiniBand in days. Train, fine-tune, and deploy LLMs on thousands of affordable GPUs in minutes with FluidStack. FluidStack unites individual data centers to overcome monopolistic GPU cloud pricing. Compute 5x faster while making the cloud efficient. Instantly access 47,000+ unused servers with tier 4 uptime and security from one simple interface. Train larger models, deploy Kubernetes clusters, render quicker, and stream with no latency. Setup in one click with custom images and APIs to deploy in seconds. 24/7 direct support via Slack, emails, or calls, our engineers are an extension of your team.

Virtualization Software for AI Infrastructure. Gain visibility and control over AI workloads to increase GPU utilization. Run:AI has built the world’s first virtualization layer for deep learning training models. By abstracting workloads from underlying infrastructure, Run:AI creates a shared pool of resources that can be dynamically provisioned, enabling full utilization of expensive GPU resources. Gain control over the allocation of expensive GPU resources. Run:AI’s scheduling mechanism enables IT to control, prioritize and align data science computing needs with business goals. Using Run:AI’s advanced monitoring tools, queueing mechanisms, and automatic preemption of jobs based on priorities, IT gains full control over GPU utilization. By creating a flexible ‘virtual pool’ of compute resources, IT leaders can visualize their full infrastructure capacity and utilization across sites, whether on premises or in the cloud.

Training-ready platform with NVIDIA® H100 Tensor Core GPUs. Competitive pricing. Dedicated support. Built for large-scale ML workloads: Get the most out of multihost training on thousands of H100 GPUs of full mesh connection with latest InfiniBand network up to 3.2Tb/s per host. Best value for money: Save at least 50% on your GPU compute compared to major public cloud providers*. Save even more with reserves and volumes of GPUs. Onboarding assistance: We guarantee a dedicated engineer support to ensure seamless platform adoption. Get your infrastructure optimized and k8s deployed. Fully managed Kubernetes: Simplify the deployment, scaling and management of ML frameworks on Kubernetes and use Managed Kubernetes for multi-node GPU training. Marketplace with ML frameworks: Explore our Marketplace with its ML-focused libraries, applications, frameworks and tools to streamline your model training. Easy to use. We provide all our new users with a 1-month trial period.

Whether prompt engineering, fine-tuning, or training, we are ready to meet your business demands. Easily integrate your new model into your production application using the Together Inference API. With the fastest performance available and elastic scaling, Together AI is built to scale with your needs as you grow. Inspect how models are trained and what data is used to increase accuracy and minimize risks. You own the model you fine-tune, not your cloud provider. Change providers for whatever reason, including price changes. Maintain complete data privacy by storing data locally or in our secure cloud.

fal is a serverless Python runtime that lets you scale your code in the cloud with no infra management. Build real-time AI applications with lightning-fast inference (under ~120ms). Check out some of the ready-to-use models, they have simple API endpoints ready for you to start your own AI-powered applications. Ship custom model endpoints with fine-grained control over idle timeout, max concurrency, and autoscaling. Use common models such as Stable Diffusion, Background Removal, ControlNet, and more as APIs. These models are kept warm for free. (Don't pay for cold starts) Join the discussion around our product and help shape the future of AI. Automatically scale up to hundreds of GPUs and scale down back to 0 GPUs when idle. Pay by the second only when your code is running. You can start using fal on any Python project by just importing fal and wrapping existing functions with the decorator.

Launch GPU-accelerated instances highly configurable to your AI workload & budget. Reserve thousands of GPUs in a next-gen AI data center for training and inference at scale. The AI world is shifting to GPU clouds for building and launching groundbreaking models without the pain of managing infrastructure and scarcity of resources. AI-centric cloud providers outpace traditional hyperscalers on availability, compute costs and scaling GPU utilization to fit complex AI workloads. Ori houses a large pool of various GPU types tailored for different processing needs. This ensures a higher concentration of more powerful GPUs readily available for allocation compared to general-purpose clouds. Ori is able to offer more competitive pricing year-on-year, across on-demand instances or dedicated servers. When compared to per-hour or per-usage pricing of legacy clouds, our GPU compute costs are unequivocally cheaper to run large-scale AI workloads.

Up to 8 NVidia® H100 80GB GPUs, each containing 16896 CUDA cores and 528 Tensor Cores. This is the current flagship silicon from NVidia®, unbeaten in raw performance for AI operations. We deploy the SXM5 NVLINK module, which offers a memory bandwidth of 2.6 Gbps and up to 900GB/s P2P bandwidth. Fourth generation AMD Genoa, up to 384 threads with a boost clock of 3.7GHz. We only use the SXM4 'for NVLINK' module, which offers a memory bandwidth of over 2TB/s and Up to 600GB/s P2P bandwidth. Second generation AMD EPYC Rome, up to 192 threads with a boost clock of 3.3GHz. The name 8A100.176V is composed as follows: 8x RTX A100, 176 CPU core threads & virtualized. Despite having less tensor cores than the V100, it is able to process tensor operations faster due to a different architecture. Second generation AMD EPYC Rome, up to 96 threads with a boost clock of 3.35GHz.

Launch immediately, preconfigured for machine learning tasks. GPUs are in high demand with the current AI wave. If you own GPUs, you can make use of them to earn massive returns on investment (40% to 150%) by renting them out to AI companies, universities, and hobbyists. Rent out your GPUs with a few simple clicks and benefit from high utilization rates. GPUDeploy offers low-cost on-demand GPUs for machine learning and AI. You can also connect and manage your GPUs to earn money.

Simplify your cloud infrastructure with our Linux virtual machines and robust set of tools to develop, deploy, and scale your modern applications faster and easier. Linode believes that in order to accelerate innovation in the cloud, virtual computing must be more accessible, affordable, and simple. Our infrastructure-as-a-service platform is deployed across 11 global markets from our data centers around the world and is supported by our Next Generation Network, advanced APIs, comprehensive services, and vast library of educational resources. Linode products, services, and people enable developers and businesses to build, deploy, and scale applications more easily and cost-effectively in the cloud.

Migrate your business- and mission-critical workloads to Azure infrastructure and improve operational efficiency. Run SQL Server, SAP, Oracle® software and high-performance computing applications on Azure Virtual Machines. Choose your favorite Linux distribution or Windows Server. Deploy virtual machines featuring up to 416 vCPUs and 12 TB of memory. Get up to 3.7 million local storage IOPS per VM. Take advantage of up to 30 Gbps Ethernet and cloud’s first deployment of 200 Gbps InfiniBand. Select the underlying processors – AMD, Ampere (Arm-based), or Intel - that best meet your requirements. Encrypt sensitive data, protect VMs from malicious threats, secure network traffic, and meet regulatory and compliance requirements. Use Virtual Machine Scale Sets to build scalable applications. Reduce your cloud spend with Azure Spot Virtual Machines and reserved instances. Build your private cloud with Azure Dedicated Host. Run mission-critical applications in Azure to increase resiliency.

Persistence container technology enables lightweight operation. Pay-per-use in seconds rather than hours or months. Fees will be paid by credit card in the next month. High performance, but low price compared to others. Will be installed in the world's fastest supercomputer by Oak Ridge National Laboratory. Machine learning applications like deep learning, computational fluid dynamics, video encoding, 3D graphics workstation, 3D rendering, VFX, computational finance, seismic analysis, molecular modeling, genomics, and other server-side GPU computation workloads.

Whether you're creating machine learning models or conducting complex data analytics, Genesis Cloud provides the accelerators for any size application. Create a GPU or CPU virtual machine in minutes. With multiple configurations, you will find an option that works for your project's size, from bootstrap to scaleout. Create storage volumes that can dynamically expand as your data grows. Backed by a highly available storage cluster and encrypted at rest, your data is secure from unexpected loss or access. Our data centers are built using a non-blocking leaf-spine architecture based on 100G switches. Each server is connected with multiple 25G uplinks and each account has its own isolated virtual network for added privacy and security. Our cloud offers you infrastructure powered by renewable energy at a price that is the most affordable in the market.

Picking the right GPU server hardware is itself a challenge. DLPerf (Deep Learning Performance) - is our own scoring function that predicts hardware performance ranking for typical deep learning tasks. We help automate and standardize the evaluation and ranking of myriad hardware platforms from dozens of datacenters and hundreds of providers. Today most of the world's general compute power consists of GPUs used for cryptocurrency mining or gaming. Due to new ASICs and other shifts in the ecosystem causing declining profits these GPUs need new uses. Vast simplifies the process of renting out machines, allowing anyone to become a cloud compute provider resulting in much lower prices. XFA AI gives you control over the level of security you require for your tasks. From lower-cost hobbyist providers with consumer GPUs up to Tier 4 data centers with enterprise GPUs, Vast.ai lets you choose providers to meet your security needs.

Cloudalize GPU-powered solutions deliver agility, flexibility and security for IIoT, Machine Learning, remote working and more. Cloudalize offers a full-range of GPU-powered Cloud solutions for your business to unlock it’s real potential. Cloudalize’s GPU-powered Desktop-as-a-Service (DaaS) solution is all you need to design and render what you want with a large range of professional software from your preferred vendors. Our DaaS solution boots in minutes and offers a convenient and inexpensive way for companies to focus on collaboration and remote working from anywhere and on any device. It provides the unequalled processing power and a super-performant way of keeping your operations running smoothly and without risk. Cloudalize’s GPU-powered DaaS is an ideal solution for a small and medium enterprise/business and a larger organisation with thousands of end users.

Foundry is a new breed of public cloud, powered by an orchestration platform that makes accessing AI compute as easy as flipping a light switch. Explore the high-impact features of our GPU cloud services designed for maximum performance and reliability. Whether you’re managing training runs, serving clients, or meeting research deadlines. Industry giants have invested for years in infra teams that build sophisticated cluster management and workload orchestration tools to abstract away the hardware. Foundry makes this accessible to everyone else, ensuring that users can reap compute leverage without a twenty-person team at scale. The current GPU ecosystem is first-come, first-serve, and fixed-price. Availability is a challenge in peak times, and so are the puzzling gaps in rates across vendors. Foundry is powered by a sophisticated mechanism design that delivers better price performance than anyone on the market.

Vast.ai is the market leader in low-cost cloud GPU rental. Use one simple interface to save 5-6X on GPU compute. Use on-demand rentals for convenience and consistent pricing. Or save a further 50% or more with interruptible instances using spot auction based pricing. Vast has an array of providers that offer different levels of security: from hobbyists up to Tier-4 data centers. Vast.ai helps you find the best pricing for the level of security and reliability you need. Use our command line interface to search the entire marketplace for offers while utilizing scriptable filters and sort options. Launch instances quickly right from the CLI and easily automate your deployment. Save an additional 50% or more by using interruptible instances and auction pricing. The highest bidding instances run; other conflicting instances are stopped.

Options for every business to train deep learning and machine learning models cost-effectively. AI accelerators for every use case, from low-cost inference to high-performance training. Simple to get started with a range of services for development and deployment. Tensor Processing Units (TPUs) are custom-built ASIC to train and execute deep neural networks. Train and run more powerful and accurate models cost-effectively with faster speed and scale. A range of NVIDIA GPUs to help with cost-effective inference or scale-up or scale-out training. Leverage RAPID and Spark with GPUs to execute deep learning. Run GPU workloads on Google Cloud where you have access to industry-leading storage, networking, and data analytics technologies. Access CPU platforms when you start a VM instance on Compute Engine. Compute Engine offers a range of both Intel and AMD processors for your VMs.

A new way to automatically train, evaluate and deploy state-of-the-art Machine Learning models. AutoTrain is an automatic way to train and deploy state-of-the-art Machine Learning models, seamlessly integrated with the Hugging Face ecosystem. Your training data stays on our server, and is private to your account. All data transfers are protected with encryption. Available today: text classification, text scoring, entity recognition, summarization, question answering, translation and tabular. CSV, TSV or JSON files, hosted anywhere. We delete your training data after training is done. Hugging Face also hosts an AI content detection tool.

Machine learning has produced business and research breakthroughs ranging from network security to medical diagnoses. We built the Tensor Processing Unit (TPU) in order to make it possible for anyone to achieve similar breakthroughs. Cloud TPU is the custom-designed machine learning ASIC that powers Google products like Translate, Photos, Search, Assistant, and Gmail. Here’s how you can put the TPU and machine learning to work accelerating your company’s success, especially at scale. Cloud TPU is designed to run cutting-edge machine learning models with AI services on Google Cloud. And its custom high-speed network offers over 100 petaflops of performance in a single pod, enough computational power to transform your business or create the next research breakthrough. Training machine learning models is like compiling code: you need to update often, and you want to do so as efficiently as possible. ML models need to be trained over and over as apps are built, deployed, and refined.

Oracle Cloud Infrastructure provides fast, flexible, and affordable compute capacity to fit any workload need from performant bare metal servers and VMs to lightweight containers. OCI Compute provides uniquely flexible VM and bare metal instances for optimal price-performance. Select exactly the number of cores and the memory your applications need. Delivering high performance for enterprise workloads. Simplify application development with serverless computing. Your choice of technologies includes Kubernetes and containers. NVIDIA GPUs for machine learning, scientific visualization, and other graphics processing. Capabilities such as RDMA, high-performance storage, and network traffic isolation. Oracle Cloud Infrastructure consistently delivers better price performance than other cloud providers. Virtual machine-based (VM) shapes offer customizable core and memory combinations. Customers can optimize costs by choosing a specific number of cores.

Elastic computing instances with GPU computing accelerators suitable for scenarios (such as artificial intelligence (specifically deep learning and machine learning), high-performance computing, and professional graphics processing). Elastic GPU Service provides a complete service system that combines software and hardware to help you flexibly allocate resources, elastically scale your system, improve computing power, and lower the cost of your AI-related business. It applies to scenarios (such as deep learning, video encoding and decoding, video processing, scientific computing, graphical visualization, and cloud gaming). Elastic GPU Service provides GPU-accelerated computing capabilities and ready-to-use, scalable GPU computing resources. GPUs have unique advantages in performing mathematical and geometric computing, especially floating-point and parallel computing. GPUs provide 100 times the computing power of their CPU counterparts.

Access readily available dedicated machines with pre-configured professional AI development tools, from dependable data centers at competitive prices. From HPC resources to an all-in-one AI platform with an integrated ML development toolkit, Apolo covers it all. Apolo can be deployed in a distributed architecture, as a dedicated enterprise cluster, or as a multi-tenant white-label solution to support dedicated instances or self-service cloud. Right out of the box, Apolo spins up a full-fledged AI-centric development environment with all the tools you need at your fingertips. Apolo manages and automates the infrastructure and processes for successful AI development at scale. Apolo's AI-centric services seamlessly stitch your on-prem and cloud resources, deploy pipelines, and integrate your open-source and commercial development tools. Apolo empowers enterprises with the tools and resources necessary to achieve breakthroughs in AI.

Conventional CPUs can no longer cope with the increased demand for computing power. GPU processors exceed the data processing speed of conventional CPUs by 100-200 times. We provide servers that are specifically designed for machine learning and deep learning purposes and are equipped with distinctive features. Modern hardware based on the NVIDIA® GPU chipset, which has a high operation speed. The newest Tesla® V100 cards with their high processing power. Optimized for deep learning software, TensorFlow™, Caffe2, Torch, Theano, CNTK, MXNet™. Includes development tools based on the programming languages ​​Python 2, Python 3, and C++. We do not charge fees for every extra service. This means disk space and traffic are already included in the cost of the basic services package. In addition, our servers can be used for various tasks of video processing, rendering, etc. LeaderGPU® customers can now use a graphical interface via RDP out of the box.

iRender Render Farm is a Powerful GPU-Acceleration Cloud Rendering for (Redshift, Octane, Blender, V-Ray (RT), Arnold GPU, UE5, Iray, Omniverse etc.) Multi-GPU Rendering tasks. Rent servers in the IaaS Render Farm model (Infrastructure as a Service) at your disposition and enjoy working with a scalable infrastructure. iRender provides High-performance machines for GPU-based & CPU-based rendering on the cloud. Designers, artists, or architects like you can leverage the power of single GPU, multi GPUs or CPU machines to speed up your render time. You get access to the remote server easily via an RDP file; take full control of it and install any 3D design software, render engines & 3D plugins you want on it. In addition, iRender also supports the majority of the well-known AI IDEs and AI frameworks to help you optimize your AI workflow.

At NumGenius AI, we are committed to redefining the enterprise server rental landscape. Our mission is to deliver state-of-the-art server solutions that are not only technologically advanced but also tailored to meet the evolving needs of businesses across various industries. Invest in NumGenius AI, achieve wealth growth. More Cloud, Less Money. NumGenius AI offers globally available, enterprise-grade infrastructure, for just a fraction the cost of the Big Tech clouds. Cloud Compute These NumGenius AI machines run atop shared vCPUs, and are suitable for many business and personal applications: low traffic websites, blogs, CMS, dev/test environments, small databases, and much more. Choose High Performance or High Frequency plans for the newer generations of AMD or Intel CPUs, along with NVMe SSD.

Begin your online journey with Cyfuture Cloud, offering fast and secure web hosting to help you excel in the digital world. Cyfuture Cloud provides a variety of web hosting services, including Domain Registration, Cloud Hosting, Email Hosting, SSL Certificates, and LiteSpeed Servers. Additionally, our GPU cloud server services, powered by NVIDIA, are ideal for handling AI, machine learning, and big data analytics, ensuring top performance and efficiency. Choose Cyfuture Cloud if you are looking for: 🚀 User-friendly custom control panel 🚀 24/7 expert live chat support 🚀 High-speed and reliable cloud hosting 🚀 99.9% uptime guarantee 🚀 Cost-effective pricing options

We help you slash cloud costs so you can focus on building amazing solutions. Spin the globe and point at the map, NodeShift is available there too. Regardless of where you deploy, benefit from increased privacy. Your data is up and running even if an entire country’s electricity grid goes down. The ideal way for organizations young and old to ease their way into the distributed and affordable cloud at their own pace. The most affordable compute and GPU virtual machines at scale. The NodeShift platform aggregates multiple independent data centers across the world and a wide range of existing decentralized solutions under one hood such as Akash, Filecoin, ThreeFold, and many more, with an emphasis on affordable prices and a friendly UX. Payment for its cloud services is simple and straightforward, giving every business access to the same interfaces as the traditional cloud but with several key added benefits of decentralization such as affordability, privacy, and resilience.

We listened and lowered our bare metal and virtual server prices. Same power and flexibility. A graphics processing unit (GPU) is “extra brain power” the CPU lacks. Choosing IBM Cloud® for your GPU requirements gives you direct access to one of the most flexible server-selection processes in the industry, seamless integration with your IBM Cloud architecture, APIs and applications, and a globally distributed network of data centers. IBM Cloud Bare Metal Servers with GPUs perform better on 5 TensorFlow ML models than AWS servers. We offer bare metal GPUs and virtual server GPUs. Google Cloud only offers virtual server instances. Like Google Cloud, Alibaba Cloud only offers GPU options on virtual machines.

Harness the power of global GPU resources with a single click. Instant, permissionless access to a global network of GPUs and CPUs. Spend significantly less on your GPU computing compared to the major public clouds or buying your own servers. Engage with the io.net cloud, customize your selection, and deploy within a matter of seconds. Get refunded whenever you choose to terminate your cluster, and always have access to a mix of cost and performance. Turn your GPU into a money-making machine with io.net, Our easy-to-use platform allows you to easily rent out your GPU. Profitable, transparent, and simple. Join the world's largest network of GPU clusters with sky-high returns. Earn significantly more on your GPU compute compared to even the best crypto mining pools. Always know how much you will earn and get paid the second the job is done. The more you invest in your infrastructure, the higher your returns are going to be.

With a click of the button open your own high performance PC, on any device, anywhere and anytime. Perform smoothly with up to 96 x 2.8 Ghz, 1360 GB of RAM and 16 x NVIDIA A100 80 GB. Enlarge storage space and computer specs as you need. We keep it simple, so you can focus on what’s really important - your projects. Pick one of our plans, depending 
if you want to use the Cloud PC individually or in a team. Decide what hardware setup you want to work with. Work on your Cloud Desktop within your browser or in the desktop app, regardless where you are. Renderro Cloud Storage lets you store all your top-notch designs and resources in a single, easily accessible place. The Cloud Storage is scalable, which means you are not limited by the file size of your projects, and can always manage the storage size at any time. Cloud Drives can be shared between multiple Cloud Desktops, giving you a way to quickly switch between machines, without the need to transfer your media back and forth.

GrapixAI is Southeast Asia's leading big data and artificial intelligence company, focusing on artificial intelligence server solutions and providing services such as GPU rental, cloud computing, and AI deep learning. The service areas cover financial services, technology, medical care, payment, e-commerce and other industries.

A modern, Kubernetes native cloud that’s purpose-built for large scale, GPU-accelerated workloads. Designed with engineers and innovators in mind, CoreWeave offers unparalleled access to a broad range of compute solutions that are up to 35x faster and 80% less expensive than legacy cloud providers. Each component of our infrastructure has been carefully designed to help our clients access the scale and variety of compute they need to create and innovate. One of our core differentiators is the freedom and power we give our clients to scale up and scale down in seconds. Strict resource quotas and waiting hours for GPUs to spin up is a thing of the past, and we’re always ready to meet demand. When we say you can tap into thousands of GPUs in seconds, we mean it. We price compute appropriately and provide the flexibility for you to configure your instances to meet the requirements of your deployments.

We build cloud infrastructures tailored to your needs. We support you in all the phases of your business, from the analysis of the best IT infrastructure to the migration, and in cases of complex architectures. Time is money, and this is even truer when you work in the IT field. Save your time and choose the best quality hosting and cloud services with great support and rapid customer service. Our state-of-the-art data centers are located in Milan, Sesto San Giovanni, Lugano, and Frosinone. We use only high-quality, name-brand hardware. We offer the maximum security to deliver a robust and highly available IT infrastructure, enabling you to recover your workloads quickly. Seeweb cloud solutions are sustainable and responsible. Our company policies contemplate ethics, inclusion, and our full support of projects dedicated to society and the environment. All our server farms are powered by 100% renewable energy.

OVHcloud puts complete freedom in the hands of technologists and businesses, for anyone to master right from the start. We are a global technology company serving developers, entrepreneurs, and businesses with dedicated server, software and infrastructure building blocks to manage, secure, and scale their data. Throughout our history, we have always challenged the status quo and set out to make technology accessible and affordable. In our rapidly evolving digital world, we believe an integral part of our future is an open ecosystem and open cloud, where all can continue to thrive and customers can choose when, where and how to manage their data. We are a global company trusted by more than 1.5 million customers. We manufacture our servers, own and manage 30 data centers, and operate our own fiber-optic network. From our range of products, our support, thriving ecosystem, and passionate employees, to our commitment to social responsibility—we are open to power your data.

Accelerate the end-to-end machine learning lifecycle. Empower developers and data scientists with a wide range of productive experiences for building, training, and deploying machine learning models faster. Accelerate time to market and foster team collaboration with industry-leading MLOps—DevOps for machine learning. Innovate on a secure, trusted platform, designed for responsible ML. Productivity for all skill levels, with code-first and drag-and-drop designer, and automated machine learning. Robust MLOps capabilities that integrate with existing DevOps processes and help manage the complete ML lifecycle. Responsible ML capabilities – understand models with interpretability and fairness, protect data with differential privacy and confidential computing, and control the ML lifecycle with audit trials and datasheets. Best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R.

Wallaroo facilitates the last-mile of your machine learning journey, getting ML into your production environment to impact the bottom line, with incredible speed and efficiency. Wallaroo is purpose-built from the ground up to be the easy way to deploy and manage ML in production, unlike Apache Spark, or heavy-weight containers. ML with up to 80% lower cost and easily scale to more data, more models, more complex models. Wallaroo is designed to enable data scientists to quickly and easily deploy their ML models against live data, whether to testing environments, staging, or prod. Wallaroo supports the largest set of machine learning training frameworks possible. You’re free to focus on developing and iterating on your models while letting the platform take care of deployment and inference at speed and scale.

The RAPIDS suite of software libraries, built on CUDA-X AI, gives you the freedom to execute end-to-end data science and analytics pipelines entirely on GPUs. It relies on NVIDIA® CUDA® primitives for low-level compute optimization, but exposes that GPU parallelism and high-bandwidth memory speed through user-friendly Python interfaces. RAPIDS also focuses on common data preparation tasks for analytics and data science. This includes a familiar DataFrame API that integrates with a variety of machine learning algorithms for end-to-end pipeline accelerations without paying typical serialization costs. RAPIDS also includes support for multi-node, multi-GPU deployments, enabling vastly accelerated processing and training on much larger dataset sizes. Accelerate your Python data science toolchain with minimal code changes and no new tools to learn. Increase machine learning model accuracy by iterating on models faster and deploying them more frequently.