Alternatives to Brev.dev
Compare Brev.dev alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Brev.dev in 2025. Compare features, ratings, user reviews, pricing, and more from Brev.dev competitors and alternatives in order to make an informed decision for your business.
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Vultr
Vultr
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. -
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BentoML
BentoML
Serve your ML model in any cloud in minutes. Unified model packaging format enabling both online and offline serving on any platform. 100x the throughput of your regular flask-based model server, thanks to our advanced micro-batching mechanism. Deliver high-quality prediction services that speak the DevOps language and integrate perfectly with common infrastructure tools. Unified format for deployment. High-performance model serving. DevOps best practices baked in. The service uses the BERT model trained with the TensorFlow framework to predict movie reviews' sentiment. DevOps-free BentoML workflow, from prediction service registry, deployment automation, to endpoint monitoring, all configured automatically for your team. A solid foundation for running serious ML workloads in production. Keep all your team's models, deployments, and changes highly visible and control access via SSO, RBAC, client authentication, and auditing logs.Starting Price: Free -
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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 -
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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 -
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fal.ai
fal.ai
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.Starting Price: $0.00111 per second -
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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 -
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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 -
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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 -
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Civo
Civo
Setup should be easy. We've listened to real user feedback from our community to simplify the developer experience. Our billing model has been designed from scratch for cloud-native, only pay for the resources you need, with no surprises. Boost productivity through industry-leading launch times. Accelerate development cycles, innovate, and deliver results faster. Blazing fast, simplified, managed Kubernetes. Host your applications and scale as and when you need them, with 90-second cluster launch times and a free control plane. Enterprise-class compute instances powered by Kubernetes. With multi-region support, DDoS protection, bandwidth pooling, and all the developer tools you need. A fully managed, auto-scaling machine learning environment. No Kubernetes or ML expertise is needed. Effortlessly set up and scale managed databases straight from your Civo dashboard or via our developer API. Scale up and down as you need, only pay for what you use.Starting Price: $250 per month -
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Nscale
Nscale
Nscale is the Hyperscaler engineered for AI, offering high-performance computing optimized for training, fine-tuning, and intensive workloads. From our data centers to our software stack, we are vertically integrated in Europe to provide unparalleled performance, efficiency, and sustainability. Access thousands of GPUs tailored to your requirements using our AI cloud platform. Reduce costs, grow revenue, and run your AI workloads more efficiently on a fully integrated platform. Whether you're using Nscale's built-in AI/ML tools or your own, our platform is designed to simplify the journey from development to production. The Nscale Marketplace offers users access to various AI/ML tools and resources, enabling efficient and scalable model development and deployment. Serverless allows seamless, scalable AI inference without the need to manage infrastructure. It automatically scales to meet demand, ensuring low latency and cost-effective inference for popular generative AI models. -
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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. -
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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 -
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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 -
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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. -
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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 -
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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 -
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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 -
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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. -
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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 -
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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 our 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 -
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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 -
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Google Cloud GPUs
Google
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.Starting Price: $0.160 per GPU -
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NeevCloud
NeevCloud
NeevCloud delivers cutting-edge GPU cloud solutions powered by NVIDIA GPUs like the H200, H100, GB200 NVL72, and many more offering unmatched performance for AI, HPC, and data-intensive workloads. Scale dynamically with flexible pricing and energy-efficient GPUs that reduce costs while maximizing output. Ideal for AI model training, scientific research, media production, and real-time analytics, NeevCloud ensures seamless integration and global accessibility. Experience unparalleled speed, scalability, and sustainability with NeevCloud GPU cloud solutions.Starting Price: $1.69/GPU/hour -
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Krutrim Cloud
Krutrim
Ola Krutrim is an AI-driven platform offering a comprehensive suite of services designed to advance artificial intelligence applications across various sectors. Their offerings include scalable cloud infrastructure, AI model deployment, and India's first domestically designed AI chips. The platform supports AI workloads with GPU acceleration, enabling efficient training and inference processes. Additionally, Ola Krutrim provides AI-enhanced mapping solutions, seamless language translation services, and AI-powered customer support chatbots. Our AI studio allows users to deploy cutting-edge AI models effortlessly, while the Language Hub offers translation, transliteration, and speech-to-text conversion capabilities. Ola Krutrim's mission is to empower India's 1.4 billion+ consumers, developers, entrepreneurs, and enterprises by putting the power of AI in their hands. -
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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. -
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Provision a VM quickly with everything you need to get your deep learning project started on Google Cloud. Deep Learning VM Image makes it easy and fast to instantiate a VM image containing the most popular AI frameworks on a Google Compute Engine instance without worrying about software compatibility. You can launch Compute Engine instances pre-installed with TensorFlow, PyTorch, scikit-learn, and more. You can also easily add Cloud GPU and Cloud TPU support. Deep Learning VM Image supports the most popular and latest machine learning frameworks, like TensorFlow and PyTorch. To accelerate your model training and deployment, Deep Learning VM Images are optimized with the latest NVIDIA® CUDA-X AI libraries and drivers and the Intel® Math Kernel Library. Get started immediately with all the required frameworks, libraries, and drivers pre-installed and tested for compatibility. Deep Learning VM Image delivers a seamless notebook experience with integrated support for JupyterLab.
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Amazon EC2 P5 Instances
Amazon
Amazon Elastic Compute Cloud (Amazon EC2) P5 instances, powered by NVIDIA H100 Tensor Core GPUs, and P5e and P5en instances powered by NVIDIA H200 Tensor Core GPUs deliver the highest performance in Amazon EC2 for deep learning and high-performance computing applications. They help you accelerate your time to solution by up to 4x compared to previous-generation GPU-based EC2 instances, and reduce the cost to train ML models by up to 40%. These instances help you iterate on your solutions at a faster pace and get to market more quickly. You can use P5, P5e, and P5en instances for training and deploying increasingly complex large language models and diffusion models powering the most demanding generative artificial intelligence applications. These applications include question-answering, code generation, video and image generation, and speech recognition. You can also use these instances to deploy demanding HPC applications at scale for pharmaceutical discovery. -
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Barbara
Barbara
Barbara is the Edge AI Platform for organizations looking to overcome the challenges of deploying AI, in mission-critical environments. With Barbara companies can deploy, train and maintain their models across thousands of devices in an easy fashion, with the autonomy, privacy and real- time that the cloud can´t match. Barbara technology stack is composed by: .- Industrial Connectors for legacy or next-generation equipment. .- Edge Orchestrator to deploy and control container-based and native edge apps across thousands of distributed locations .- MLOps to optimize, deploy, and monitor your trained model in minutes. .- Marketplace of certified Edge Apps, ready to be deployed. .- Remote Device Management for provisioning, configuration, and updates. More --> www. barbara.tech -
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Amazon EC2 Trn1 Instances
Amazon
Amazon Elastic Compute Cloud (EC2) Trn1 instances, powered by AWS Trainium chips, are purpose-built for high-performance deep learning training of generative AI models, including large language models and latent diffusion models. Trn1 instances offer up to 50% cost-to-train savings over other comparable Amazon EC2 instances. You can use Trn1 instances to train 100B+ parameter DL and generative AI models across a broad set of applications, such as text summarization, code generation, question answering, image and video generation, recommendation, and fraud detection. The AWS Neuron SDK helps developers train models on AWS Trainium (and deploy models on the AWS Inferentia chips). It integrates natively with frameworks such as PyTorch and TensorFlow so that you can continue using your existing code and workflows to train models on Trn1 instances.Starting Price: $1.34 per hour -
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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 -
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Burncloud
Burncloud
Burncloud is a leading cloud computing service provider focused on delivering efficient, reliable, and secure GPU rental solutions for businesses. Our platform operates on a systemized model designed to meet the high-performance computing needs of various enterprises. Core Services Online GPU Rental Services: We offer a variety of GPU models for rent, including data center-grade devices and edge consumer-level computing equipment, to meet the diverse computational needs of businesses. Our best-selling products currently include: RTX 4070, RTX 3070 Ti, H100 PCIe, RTX 3090 Ti, RTX 3060, NVIDIA 4090, L40, RTX 3080 Ti, L40S, RTX 4090, RTX 3090, A10, H100 SXM, H100 NVL, A100 PCIe 80GB, and more. Compute Cluster Setup Services: Our technical team has extensive experience in IB networking technology and has successfully completed the setup of five 256-node clusters. For cluster setup services, please contact the customer service team on the Burncloud official website.Starting Price: $0.03/hour -
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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.
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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). -
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NVIDIA RAPIDS
NVIDIA
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. -
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VESSL AI
VESSL AI
Build, train, and deploy models faster at scale with fully managed infrastructure, tools, and workflows. Deploy custom AI & LLMs on any infrastructure in seconds and scale inference with ease. Handle your most demanding tasks with batch job scheduling, only paying with per-second billing. Optimize costs with GPU usage, spot instances, and built-in automatic failover. Train with a single command with YAML, simplifying complex infrastructure setups. Automatically scale up workers during high traffic and scale down to zero during inactivity. Deploy cutting-edge models with persistent endpoints in a serverless environment, optimizing resource usage. Monitor system and inference metrics in real-time, including worker count, GPU utilization, latency, and throughput. Efficiently conduct A/B testing by splitting traffic among multiple models for evaluation.Starting Price: $100 + compute/month -
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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. -
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Neysa Nebula
Neysa
Nebula allows you to deploy and scale your AI projects quickly, easily and cost-efficiently2 on highly robust, on-demand GPU infrastructure. Train and infer your models securely and easily on the Nebula cloud powered by the latest on-demand Nvidia GPUs and create and manage your containerized workloads through Nebula’s user-friendly orchestration layer. Access Nebula’s MLOps and low-code/no-code engines to build and deploy AI use cases for business teams and to deploy AI-powered applications swiftly and seamlessly with little to no coding. Choose between the Nebula containerized AI cloud, your on-prem environment, or any cloud of your choice. Build and scale AI-enabled business use-cases within a matter of weeks, not months, with the Nebula Unify platform.Starting Price: $0.12 per hour -
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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 -
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Apolo
Apolo
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.Starting Price: $5.35 per hour -
40
Genesis Cloud
Genesis Cloud
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. -
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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.
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Pipeshift
Pipeshift
Pipeshift is a modular orchestration platform designed to facilitate the building, deployment, and scaling of open source AI components, including embeddings, vector databases, large language models, vision models, and audio models, across any cloud environment or on-premises infrastructure. The platform offers end-to-end orchestration, ensuring seamless integration and management of AI workloads, and is 100% cloud-agnostic, providing flexibility in deployment. With enterprise-grade security, Pipeshift addresses the needs of DevOps and MLOps teams aiming to establish production pipelines in-house, moving beyond experimental API providers that may lack privacy considerations. Key features include an enterprise MLOps console for managing various AI workloads such as fine-tuning, distillation, and deployment; multi-cloud orchestration with built-in auto-scalers, load balancers, and schedulers for AI models; and Kubernetes cluster management. -
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Azure Data Science Virtual Machines
Microsoft
DSVMs are Azure Virtual Machine images, pre-installed, configured and tested with several popular tools that are commonly used for data analytics, machine learning and AI training. Consistent setup across team, promote sharing and collaboration, Azure scale and management, Near-Zero Setup, full cloud-based desktop for data science. Quick, Low friction startup for one to many classroom scenarios and online courses. Ability to run analytics on all Azure hardware configurations with vertical and horizontal scaling. Pay only for what you use, when you use it. Readily available GPU clusters with Deep Learning tools already pre-configured. Examples, templates and sample notebooks built or tested by Microsoft are provided on the VMs to enable easy onboarding to the various tools and capabilities such as Neural Networks (PYTorch, Tensorflow, etc.), Data Wrangling, R, Python, Julia, and SQL Server.Starting Price: $0.005 -
44
Amazon EC2 P4 Instances
Amazon
Amazon EC2 P4d instances deliver high performance for machine learning training and high-performance computing applications in the cloud. Powered by NVIDIA A100 Tensor Core GPUs, they offer industry-leading throughput and low-latency networking, supporting 400 Gbps instance networking. P4d instances provide up to 60% lower cost to train ML models, with an average of 2.5x better performance for deep learning models compared to previous-generation P3 and P3dn instances. Deployed in hyperscale clusters called Amazon EC2 UltraClusters, P4d instances combine high-performance computing, networking, and storage, enabling users to scale from a few to thousands of NVIDIA A100 GPUs based on project needs. Researchers, data scientists, and developers can utilize P4d instances to train ML models for use cases such as natural language processing, object detection and classification, and recommendation engines, as well as to run HPC applications like pharmaceutical discovery and more.Starting Price: $11.57 per hour -
45
NetApp AIPod
NetApp
NetApp AIPod is a comprehensive AI infrastructure solution designed to streamline the deployment and management of artificial intelligence workloads. By integrating NVIDIA-validated turnkey solutions, such as NVIDIA DGX BasePOD™ and NetApp's cloud-connected all-flash storage, AIPod consolidates analytics, training, and inference capabilities into a single, scalable system. This convergence enables organizations to rapidly implement AI workflows, from model training to fine-tuning and inference, while ensuring robust data management and security. With preconfigured infrastructure optimized for AI tasks, NetApp AIPod reduces complexity, accelerates time to insights, and supports seamless integration into hybrid cloud environments. -
46
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 -
47
Amazon SageMaker Debugger
Amazon
Optimize ML models by capturing training metrics in real-time and sending alerts when anomalies are detected. Automatically stop training processes when the desired accuracy is achieved to reduce the time and cost of training ML models. Automatically profile and monitor system resource utilization and send alerts when resource bottlenecks are identified to continuously improve resource utilization. Amazon SageMaker Debugger can reduce troubleshooting during training from days to minutes by automatically detecting and alerting you to remediate common training errors such as gradient values becoming too large or too small. Alerts can be viewed in Amazon SageMaker Studio or configured through Amazon CloudWatch. Additionally, the SageMaker Debugger SDK enables you to automatically detect new classes of model-specific errors such as data sampling, hyperparameter values, and out-of-bound values. -
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MosaicML
MosaicML
Train and serve large AI models at scale with a single command. Point to your S3 bucket and go. We handle the rest, orchestration, efficiency, node failures, and infrastructure. Simple and scalable. MosaicML enables you to easily train and deploy large AI models on your data, in your secure environment. Stay on the cutting edge with our latest recipes, techniques, and foundation models. Developed and rigorously tested by our research team. With a few simple steps, deploy inside your private cloud. Your data and models never leave your firewalls. Start in one cloud, and continue on another, without skipping a beat. Own the model that's trained on your own data. Introspect and better explain the model decisions. Filter the content and data based on your business needs. Seamlessly integrate with your existing data pipelines, experiment trackers, and other tools. We are fully interoperable, cloud-agnostic, and enterprise proved. -
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Klu
Klu
Klu.ai is a Generative AI platform that simplifies the process of designing, deploying, and optimizing AI applications. Klu integrates with your preferred Large Language Models, incorporating data from varied sources, giving your applications unique context. Klu accelerates building applications using language models like Anthropic Claude, Azure OpenAI, GPT-4, and over 15 other models, allowing rapid prompt/model experimentation, data gathering and user feedback, and model fine-tuning while cost-effectively optimizing performance. Ship prompt generations, chat experiences, workflows, and autonomous workers in minutes. Klu provides SDKs and an API-first approach for all capabilities to enable developer productivity. Klu automatically provides abstractions for common LLM/GenAI use cases, including: LLM connectors, vector storage and retrieval, prompt templates, observability, and evaluation/testing tooling.Starting Price: $97 -
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The single development environment for the entire data science workflow. Natively analyze your data with a reduction in context switching between services. Data to training at scale. Build and train models 5X faster, compared to traditional notebooks. Scale-up model development with simple connectivity to Vertex AI services. Simplified access to data and in-notebook access to machine learning with BigQuery, Dataproc, Spark, and Vertex AI integration. Take advantage of the power of infinite computing with Vertex AI training for experimentation and prototyping, to go from data to training at scale. Using Vertex AI Workbench you can implement your training, and deployment workflows on Vertex AI from one place. A Jupyter-based fully managed, scalable, enterprise-ready compute infrastructure with security controls and user management capabilities. Explore data and train ML models with easy connections to Google Cloud's big data solutions.Starting Price: $10 per GB
