Alternatives to Google Cloud GPUs
Compare Google Cloud GPUs alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Google Cloud GPUs in 2024. Compare features, ratings, user reviews, pricing, and more from Google Cloud GPUs competitors and alternatives in order to make an informed decision for your business.
-
1
Amazon EC2
Amazon
Amazon Elastic Compute Cloud (Amazon EC2) is a web service that provides secure, resizable compute capacity in the cloud. It is designed to make web-scale cloud computing easier for developers. Amazon EC2’s simple web service interface allows you to obtain and configure capacity with minimal friction. It provides you with complete control of your computing resources and lets you run on Amazon’s proven computing environment. Amazon EC2 delivers the broadest choice of compute, networking (up to 400 Gbps), and storage services purpose-built to optimize price performance for ML projects. Build, test, and sign on-demand macOS workloads. Access environments in minutes, dynamically scale capacity as needed, and benefit from AWS’s pay-as-you-go pricing. Access the on-demand infrastructure and capacity you need to run HPC applications faster and cost-effectively. Amazon EC2 delivers secure, reliable, high-performance, and cost-effective compute infrastructure to meet demanding business needs. -
2
Elastic GPU Service
Alibaba
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.Starting Price: $69.51 per month -
3
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.
-
4
RunPod
RunPod
RunPod is on a mission to democratize AI from the ground up. Our first goal is to bring cloud compute to all with very competitive prices without sacrificing usability, experience, or features. Secure Cloud runs in T3/T4 data centers by our trusted partners. Our close partnership comes with high reliability, redundancy, security, and fast response times to mitigate any downtimes. For any sensitive and enterprise workloads, we highly recommend Secure Cloud.Starting Price: $0.20 per hour -
5
Tencent Cloud GPU Service
Tencent
Cloud GPU Service is an elastic computing service that provides GPU computing power with high-performance parallel computing capabilities. As a powerful tool at the IaaS layer, it delivers high computing power for deep learning training, scientific computing, graphics and image processing, video encoding and decoding, and other highly intensive workloads. Improve your business efficiency and competitiveness with high-performance parallel computing capabilities. Set up your deployment environment quickly with auto-installed GPU drivers, CUDA, and cuDNN and preinstalled driver images. Accelerate distributed training and inference by using TACO Kit, an out-of-the-box computing acceleration engine provided by Tencent Cloud.Starting Price: $0.204/hour -
6
NVIDIA GPU-Optimized AMI
Amazon
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'Starting Price: $3.06 per hour -
7
Bright for Deep Learning
Nvidia
NVIDIA Bright Cluster Manager offers fast deployment and end-to-end management for heterogeneous high-performance computing (HPC) and AI server clusters at the edge, in the data center, and in multi/hybrid-cloud environments. It automates provisioning and administration for clusters ranging in size from a couple of nodes to hundreds of thousands, supports CPU-based and NVIDIA GPU-accelerated systems, and enables orchestration with Kubernetes. Heterogeneous high-performance Linux clusters can be quickly built and managed with NVIDIA Bright Cluster Manager, supporting HPC, machine learning, and analytics applications that span from core to edge to cloud. NVIDIA Bright Cluster Manager is ideal for heterogeneous environments, supporting Arm® and x86-based CPU nodes, and is fully optimized for accelerated computing with NVIDIA GPUs and NVIDIA DGX™ systems. -
8
Lambda GPU Cloud
Lambda
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.Starting Price: $1.25 per hour -
9
Runyour AI
Runyour AI
From renting machines for AI research to specialized templates and servers, Runyour AI provides the optimal environment for artificial intelligence research. Runyour AI is an AI cloud service that provides easy access to GPU resources and research environments for artificial intelligence research. You can rent various high-performance GPU machines and environments at a reasonable price. Additionally, you can register your own GPUs to generate revenue. Transparent billing policy where you pay for charging points used through minute-by-minute real-time monitoring. From casual hobbyists to seasoned researchers, we provide specialized GPUs for AI projects, catering to a range of needs. An AI project environment that is easy and convenient for even first-time users. By utilizing Runyour AI's GPU machines, you can kickstart your AI research with minimal setup. Designed for quick access to GPUs, it provides a seamless research environment for machine learning and AI development. -
10
Nebius
Nebius
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.Starting Price: $2.66/hour -
11
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.Starting Price: $0.007 per hour
-
12
Oblivus
Oblivus
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.Starting Price: $0.29 per hour -
13
Hyperstack
Hyperstack
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.Starting Price: $0.18 per GPU per hour -
14
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.
-
15
Mystic
Mystic
With Mystic you can deploy ML in your own Azure/AWS/GCP account or deploy in our shared GPU cluster. All Mystic features are directly in your own cloud. In a few simple steps, you get the most cost-effective and scalable way of running ML inference. Our shared cluster of GPUs is used by 100s of users simultaneously. Low cost but performance will vary depending on real-time GPU availability. Good AI products need good models and infrastructure; we solve the infrastructure part. A fully managed Kubernetes platform that runs in your own cloud. Open-source Python library and API to simplify your entire AI workflow. You get a high-performance platform to serve your AI models. Mystic will automatically scale up and down GPUs depending on the number of API calls your models receive. You can easily view, edit, and monitor your infrastructure from your Mystic dashboard, CLI, and APIs.Starting Price: Free -
16
Foundry
Foundry
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. -
17
FluidStack
FluidStack
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.Starting Price: $1.49 per month -
18
AWS Neuron
Amazon Web Services
It supports high-performance training on AWS Trainium-based Amazon Elastic Compute Cloud (Amazon EC2) Trn1 instances. For model deployment, it supports high-performance and low-latency inference on AWS Inferentia-based Amazon EC2 Inf1 instances and AWS Inferentia2-based Amazon EC2 Inf2 instances. With Neuron, you can use popular frameworks, such as TensorFlow and PyTorch, and optimally train and deploy machine learning (ML) models on Amazon EC2 Trn1, Inf1, and Inf2 instances with minimal code changes and without tie-in to vendor-specific solutions. AWS Neuron SDK, which supports Inferentia and Trainium accelerators, is natively integrated with PyTorch and TensorFlow. This integration ensures that you can continue using your existing workflows in these popular frameworks and get started with only a few lines of code changes. For distributed model training, the Neuron SDK supports libraries, such as Megatron-LM and PyTorch Fully Sharded Data Parallel (FSDP). -
19
Paperspace
Paperspace
CORE is a high-performance computing platform built for a range of applications. CORE offers a simple point-and-click interface that makes it simple to get up and running. Run the most demanding applications. CORE offers limitless computing power on demand. Enjoy the benefits of cloud computing without the high cost. CORE for teams includes powerful tools that let you sort, filter, create, and connect users, machines, and networks. It has never been easier to get a birds-eye view of your infrastructure in a single place with an intuitive and effortless GUI. Our simple yet powerful management console makes it easy to do things like adding a VPN or Active Directory integration. Things that used to take days or even weeks can now be done with just a few clicks and even complex network configurations become easy to manage. Paperspace is used by some of the most advanced organizations in the world.Starting Price: $5 per month -
20
NVIDIA NGC
NVIDIA
NVIDIA GPU Cloud (NGC) is a GPU-accelerated cloud platform optimized for deep learning and scientific computing. NGC manages a catalog of fully integrated and optimized deep learning framework containers that take full advantage of NVIDIA GPUs in both single GPU and multi-GPU configurations. NVIDIA train, adapt, and optimize (TAO) is an AI-model-adaptation platform that simplifies and accelerates the creation of enterprise AI applications and services. By fine-tuning pre-trained models with custom data through a UI-based, guided workflow, enterprises can produce highly accurate models in hours rather than months, eliminating the need for large training runs and deep AI expertise. Looking to get started with containers and models on NGC? This is the place to start. Private Registries from NGC allow you to secure, manage, and deploy your own assets to accelerate your journey to AI. -
21
Ori GPU Cloud
Ori
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.Starting Price: $3.24 per month -
22
Lumino
Lumino
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. -
23
Azure Virtual Machines
Microsoft
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. -
24
DataCrunch
DataCrunch
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.Starting Price: $3.01 per hour -
25
Intel oneAPI HPC Toolkit
Intel
High-performance computing (HPC) is at the core of AI, machine learning, and deep learning applications. The Intel® oneAPI HPC Toolkit (HPC Kit) delivers what developers need to build, analyze, optimize, and scale HPC applications with the latest techniques in vectorization, multithreading, multi-node parallelization, and memory optimization. This toolkit is an add-on to the Intel® oneAPI Base Toolkit, which is required for full functionality. It also includes access to the Intel® Distribution for Python*, the Intel® oneAPI DPC++/C++ C¿compiler, powerful data-centric libraries, and advanced analysis tools. Get what you need to build, test, and optimize your oneAPI projects for free. With an Intel® Developer Cloud account, you get 120 days of access to the latest Intel® hardware, CPUs, GPUs, FPGAs, and Intel oneAPI tools and frameworks. No software downloads. No configuration steps, and no installations. -
26
XRCLOUD
XRCLOUD
GPU cloud computing is a GPU-based computing service with real-time, high-speed parallel computing and floating-point computing capacity. It is ideal for various scenarios such as 3D graphics applications, video decoding, deep learning, and scientific computing. GPU instances can be managed just like a standard ECS with speed and ease, which effectively relieves computing pressures. RTX6000 GPU contains thousands of computing units and shows substantial advantages in parallel computing. For optimized deep learning, massive computing can be completed in a short time. GPU Direct seamlessly supports the transmission of big data among networks. Built-in acceleration framework, it can focus on the core tasks by quick deployment and fast instance distribution. We offer optimal cloud performance at a transparent price. The price of our cloud solution is open and cost-effective. You may choose to charge on-demand, and you can also get more discounts by subscribing to resources.Starting Price: $4.13 per month -
27
LeaderGPU
LeaderGPU
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.Starting Price: €0.14 per minute -
28
AWS Trainium
Amazon Web Services
AWS Trainium is the second-generation Machine Learning (ML) accelerator that AWS purpose built for deep learning training of 100B+ parameter models. Each Amazon Elastic Compute Cloud (EC2) Trn1 instance deploys up to 16 AWS Trainium accelerators to deliver a high-performance, low-cost solution for deep learning (DL) training in the cloud. Although the use of deep learning is accelerating, many development teams are limited by fixed budgets, which puts a cap on the scope and frequency of training needed to improve their models and applications. Trainium-based EC2 Trn1 instances solve this challenge by delivering faster time to train while offering up to 50% cost-to-train savings over comparable Amazon EC2 instances. -
29
Azure FXT Edge Filer
Microsoft
Create cloud-integrated hybrid storage that works with your existing network-attached storage (NAS) and Azure Blob Storage. This on-premises caching appliance optimizes access to data in your datacenter, in Azure, or across a wide-area network (WAN). A combination of software and hardware, Microsoft Azure FXT Edge Filer delivers high throughput and low latency for hybrid storage infrastructure supporting high-performance computing (HPC) workloads.Scale-out clustering provides non-disruptive NAS performance scaling. Join up to 24 FXT nodes per cluster to scale to millions of IOPS and hundreds of GB/s. When you need performance and scale in file-based workloads, Azure FXT Edge Filer keeps your data on the fastest path to processing resources. Managing data storage is easy with Azure FXT Edge Filer. Shift aging data to Azure Blob Storage to keep it easily accessible with minimal latency. Balance on-premises and cloud storage. -
30
Vast.ai
Vast.ai
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.Starting Price: $0.20 per hour -
31
JarvisLabs.ai
JarvisLabs.ai
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.Starting Price: $1,440 per month -
32
Run:AI
Run:AI
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. -
33
Brev.dev
Brev.dev
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.Starting Price: $0.04 per hour -
34
Banana
Banana
Banana was started based on a critical gap that we saw in the market. Machine learning is in high demand. Yet, deploying models into production is deeply technical and complex. Banana is focused on building the machine learning infrastructure for the digital economy. We're simplifying the process to deploy, making productionizing models as simple as copying and pasting an API. This enables companies of all sizes to access and leverage state-of-the-art models. We believe that the democratization of machine learning will be one of the critical components fueling the growth of companies on a global scale. We see machine learning as the biggest technological gold rush of the 21st century and Banana is positioned to provide the picks and shovels.Starting Price: $7.4868 per hour -
35
GPUonCLOUD
GPUonCLOUD
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.Starting Price: $1 per hour -
36
Amazon SageMaker Model Training reduces the time and cost to train and tune machine learning (ML) models at scale without the need to manage infrastructure. You can take advantage of the highest-performing ML compute infrastructure currently available, and SageMaker can automatically scale infrastructure up or down, from one to thousands of GPUs. Since you pay only for what you use, you can manage your training costs more effectively. To train deep learning models faster, SageMaker distributed training libraries can automatically split large models and training datasets across AWS GPU instances, or you can use third-party libraries, such as DeepSpeed, Horovod, or Megatron. Efficiently manage system resources with a wide choice of GPUs and CPUs including P4d.24xl instances, which are the fastest training instances currently available in the cloud. Specify the location of data, indicate the type of SageMaker instances, and get started with a single click.
-
37
Intel DevCloud
Intel
Intel® DevCloud offers complimentary access to a wide range of Intel® architectures to help you get instant hands-on experience with Intel® software and execute your edge, AI, high-performance computing (HPC), and rendering workloads. With preinstalled Intel® optimized frameworks, tools, and libraries, you have everything you need to fast-track your learning and project prototyping. Learn, prototype, test, and run your workloads for free on a cluster of the latest Intel® hardware and software. Learn through a new suite of curated experiences, including market vertical samples, Jupyter Notebook tutorials, and more. Build your solution in JupyterLab and test with bare metal or develop your containerized solution. Quickly bring it to Intel DevCloud for testing. Optimize your solution for a specific target edge device with the deep learning workbench and take advantage of the new, more robust telemetry dashboard.Starting Price: Free -
38
Google Cloud TPU
Google
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.Starting Price: $0.97 per chip-hour -
39
Together AI
Together AI
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.Starting Price: $0.0001 per 1k tokens -
40
GPUEater
GPUEater
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.Starting Price: $0.0992 per hour -
41
Deep Infra
Deep Infra
Powerful, self-serve machine learning platform where you can turn models into scalable APIs in just a few clicks. Sign up for Deep Infra account using GitHub or log in using GitHub. Choose among hundreds of the most popular ML models. Use a simple rest API to call your model. Deploy models to production faster and cheaper with our serverless GPUs than developing the infrastructure yourself. We have different pricing models depending on the model used. Some of our language models offer per-token pricing. Most other models are billed for inference execution time. With this pricing model, you only pay for what you use. There are no long-term contracts or upfront costs, and you can easily scale up and down as your business needs change. All models run on A100 GPUs, optimized for inference performance and low latency. Our system will automatically scale the model based on your needs.Starting Price: $0.70 per 1M input tokens -
42
NVIDIA virtual GPU
NVIDIA
NVIDIA virtual GPU (vGPU) software enables powerful GPU performance for workloads ranging from graphics-rich virtual workstations to data science and AI, enabling IT to leverage the management and security benefits of virtualization as well as the performance of NVIDIA GPUs required for modern workloads. Installed on a physical GPU in a cloud or enterprise data center server, NVIDIA vGPU software creates virtual GPUs that can be shared across multiple virtual machines, and accessed by any device, anywhere. Deliver performance virtually indistinguishable from a bare metal environment. Leverage common data center management tools such as live migration. Provision GPU resources with fractional or multi-GPU virtual machine (VM) instances. Responsive to changing business requirements and remote teams. -
43
NVIDIA Triton™ inference server delivers fast and scalable AI in production. Open-source inference serving software, Triton inference server streamlines AI inference by enabling teams deploy trained AI models from any framework (TensorFlow, NVIDIA TensorRT®, PyTorch, ONNX, XGBoost, Python, custom and more on any GPU- or CPU-based infrastructure (cloud, data center, or edge). Triton runs models concurrently on GPUs to maximize throughput and utilization, supports x86 and ARM CPU-based inferencing, and offers features like dynamic batching, model analyzer, model ensemble, and audio streaming. Triton helps developers deliver high-performance inference aTriton integrates with Kubernetes for orchestration and scaling, exports Prometheus metrics for monitoring, supports live model updates, and can be used in all major public cloud machine learning (ML) and managed Kubernetes platforms. Triton helps standardize model deployment in production.Starting Price: Free
-
44
OctoAI
OctoML
OctoAI is world-class compute infrastructure for tuning and running models that wow your users. Fast, efficient model endpoints and the freedom to run any model. Leverage OctoAI’s accelerated models or bring your own from anywhere. Create ergonomic model endpoints in minutes, with only a few lines of code. Customize your model to fit any use case that serves your users. Go from zero to millions of users, never worrying about hardware, speed, or cost overruns. Tap into our curated list of best-in-class open-source foundation models that we’ve made faster and cheaper to run using our deep experience in machine learning compilation, acceleration techniques, and proprietary model-hardware performance technology. OctoAI automatically selects the optimal hardware target, applies the latest optimization technologies, and always keeps your running models in an optimal manner. -
45
Fuzzball
CIQ
Fuzzball accelerates innovation for researchers and scientists by eliminating the burdens of infrastructure provisioning and management. Fuzzball streamlines and optimizes high-performance computing (HPC) workload design and execution. A user-friendly GUI for designing, editing, and executing HPC jobs. Comprehensive control and automation of all HPC tasks via CLI. Automated data ingress and egress with full compliance logs. Native integration with GPUs and both on-prem and cloud storage on-prem and cloud storage. Human-readable, portable workflow files that execute anywhere. CIQ’s Fuzzball modernizes traditional HPC with an API-first, container-optimized architecture. Operating on Kubernetes, it provides all the security, performance, stability, and convenience found in modern software and infrastructure. Fuzzball not only abstracts the infrastructure layer but also automates the orchestration of complex workflows, driving greater efficiency and collaboration. -
46
Xesktop
Xesktop
After the advent of GPU computing and the horizons it expanded in the worlds of Data Science, Programming and Computer Graphics came the need for access to cost-friendly and reliable GPU Server rental services. That’s why we’re here. Our powerful, dedicated GPU servers in the cloud are at your disposal for GPU 3D rendering. Xesktop high-performance servers are perfect for intense rendering workloads. Each server runs on dedicated hardware meaning you’re getting maximum GPU performance and no compromises like on typical Virtual Machines. Maximize the GPU capabilities of engines like Octane, Redshift, Cycles, or any other engine you work with. You can connect to a server or multiple servers using your existing Windows system image at any time. All images that you create are reusable. Use the server as if it were your own personal computer.Starting Price: $6 per hour -
47
GMI Cloud
GMI Cloud
Build your generative AI applications in minutes on GMI GPU Cloud. GMI Cloud is more than bare metal. Train, fine-tune, and infer state-of-the-art models. Our clusters are ready to go with scalable GPU containers and preconfigured popular ML frameworks. Get instant access to the latest GPUs for your AI workloads. Whether you need flexible on-demand GPUs or dedicated private cloud instances, we've got you covered. Maximize GPU resources with our turnkey Kubernetes software. Easily allocate, deploy, and monitor GPUs or nodes with our advanced orchestration tools. Customize and serve models to build AI applications using your data. GMI Cloud lets you deploy any GPU workload quickly and easily, so you can focus on running ML models, not managing infrastructure. Launch pre-configured environments and save time on building container images, installing software, downloading models, and configuring environment variables. Or use your own Docker image to fit your needs.Starting Price: $2.50 per hour -
48
Qubrid AI
Qubrid AI
Qubrid AI is an advanced Artificial Intelligence (AI) company with a mission to solve real world complex problems in multiple industries. Qubrid AI’s software suite comprises of AI Hub, a one-stop shop for everything AI models, AI Compute GPU Cloud and On-Prem Appliances and AI Data Connector! Train or inference industry-leading models or your own custom creations, all within a streamlined, user-friendly interface. Test and refine your models with ease, then seamlessly deploy them to unlock the power of AI in your projects. AI Hub empowers you to embark on your AI Journey, from concept to implementation, all in a single, powerful platform. Our leading cutting-edge AI Compute platform harnesses the power of GPU Cloud and On-Prem Server Appliances to efficiently develop and run next generation AI applications. Qubrid team is comprised of AI developers, researchers and partner teams all focused on enhancing this unique platform for the advancement of scientific applications.Starting Price: $0.68/hour/GPU -
49
Cyfuture Cloud
Cyfuture Cloud
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 optionsStarting Price: $8.00 per month -
50
Renderro
Renderro
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.
