Compare the Top AI Infrastructure Platforms in Australia as of October 2025 - Page 2

  • 1
    Oblivus

    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
  • 2
    Klu

    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
  • 3
    VESSL AI

    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
  • 4
    Toolhouse

    Toolhouse

    Toolhouse

    Toolhouse is the first cloud platform that allows developers to quickly build, manage, and run AI function calling. It takes care of every aspect of connecting AI to the real world, from performance optimization to prompting to integrations with all foundational models, in just three lines of code. Toolhouse provides a 1-click platform to deploy efficient actions and knowledge for AI apps with a low-latency cloud. It offers high-quality, low-latency tools hosted on reliable and scalable infrastructure, with caching and optimization of tool responses.
    Starting Price: Free
  • 5
    E2B

    E2B

    E2B

    E2B is an open source runtime designed to securely execute AI-generated code within isolated cloud sandboxes. It enables developers to integrate code interpretation capabilities into their AI applications and agents, facilitating the execution of dynamic code snippets in a controlled environment. The platform supports multiple programming languages, including Python and JavaScript, and offers SDKs for seamless integration. E2B utilizes Firecracker microVMs to ensure robust security and isolation for code execution. Developers can deploy E2B within their own infrastructure or utilize the provided cloud service. The platform is designed to be LLM-agnostic, allowing compatibility with various large language models such as OpenAI, Llama, Anthropic, and Mistral. E2B's features include rapid sandbox initialization, customizable execution environments, and support for long-running sessions up to 24 hours.
    Starting Price: Free
  • 6
    Parasail

    Parasail

    Parasail

    Parasail is an AI deployment network offering scalable, cost-efficient access to high-performance GPUs for AI workloads. It provides three primary services, serverless endpoints for real-time inference, Dedicated instances for private model deployments, and Batch processing for large-scale tasks. Users can deploy open source models like DeepSeek R1, LLaMA, and Qwen, or bring their own, with the platform's permutation engine matching workloads to optimal hardware, including NVIDIA's H100, H200, A100, and 4090 GPUs. Parasail emphasizes rapid deployment, with the ability to scale from a single GPU to clusters within minutes, and offers significant cost savings, claiming up to 30x cheaper compute compared to legacy cloud providers. It supports day-zero availability for new models and provides a self-service interface without long-term contracts or vendor lock-in.
    Starting Price: $0.80 per million tokens
  • 7
    Azure Machine Learning
    Accelerate the end-to-end machine learning lifecycle. Empower developers and data scientists with a wide range of productive experiences for building, training, and deploying machine learning models faster. Accelerate time to market and foster team collaboration with industry-leading MLOps—DevOps for machine learning. Innovate on a secure, trusted platform, designed for responsible ML. Productivity for all skill levels, with code-first and drag-and-drop designer, and automated machine learning. Robust MLOps capabilities that integrate with existing DevOps processes and help manage the complete ML lifecycle. Responsible ML capabilities – understand models with interpretability and fairness, protect data with differential privacy and confidential computing, and control the ML lifecycle with audit trials and datasheets. Best-in-class support for open-source frameworks and languages including MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R.
  • 8
    Google Deep Learning Containers
    Build your deep learning project quickly on Google Cloud: Quickly prototype with a portable and consistent environment for developing, testing, and deploying your AI applications with Deep Learning Containers. These Docker images use popular frameworks and are performance optimized, compatibility tested, and ready to deploy. Deep Learning Containers provide a consistent environment across Google Cloud services, making it easy to scale in the cloud or shift from on-premises. You have the flexibility to deploy on Google Kubernetes Engine (GKE), AI Platform, Cloud Run, Compute Engine, Kubernetes, and Docker Swarm.
  • 9
    Intel Tiber AI Studio
    Intel® Tiber™ AI Studio is a comprehensive machine learning operating system that unifies and simplifies the AI development process. The platform supports a wide range of AI workloads, providing a hybrid and multi-cloud infrastructure that accelerates ML pipeline development, model training, and deployment. With its native Kubernetes orchestration and meta-scheduler, Tiber™ AI Studio offers complete flexibility in managing on-prem and cloud resources. Its scalable MLOps solution enables data scientists to easily experiment, collaborate, and automate their ML workflows while ensuring efficient and cost-effective utilization of resources.
  • 10
    NVIDIA GPU-Optimized AMI
    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
  • 11
    NetApp AIPod
    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.
  • 12
    Google Cloud AI Infrastructure
    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.
  • 13
    Google Cloud Deep Learning VM Image
    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.
  • 14
    Amazon SageMaker Ground Truth
    Amazon SageMaker allows you to identify raw data such as images, text files, and videos; add informative labels and generate labeled synthetic data to create high-quality training data sets for your machine learning (ML) models. SageMaker offers two options, Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth, which give you the flexibility to use an expert workforce to create and manage data labeling workflows on your behalf or manage your own data labeling workflows. data labeling. If you want the flexibility to create and manage your own personal and data labeling workflows, you can use SageMaker Ground Truth. SageMaker Ground Truth is a data labeling service that makes data labeling easy and gives you the option of using human annotators via Amazon Mechanical Turk, third-party providers, or your own private staff.
    Starting Price: $0.08 per month
  • 15
    Banana

    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
  • 16
    FluidStack

    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
  • 17
    JarvisLabs.ai

    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
  • 18
    NVIDIA Brev
    NVIDIA Brev is a cloud-based platform that provides instant access to fully configured GPU environments optimized for AI and machine learning development. Its Launchables feature offers prebuilt, customizable compute setups that let developers start projects quickly without complex setup or configuration. Users can create Launchables by specifying GPU resources, Docker images, and project files, then share them easily with collaborators. The platform also offers prebuilt Launchables featuring the latest AI frameworks, microservices, and NVIDIA Blueprints to jumpstart development. NVIDIA Brev provides a seamless GPU sandbox with support for CUDA, Python, and Jupyter Lab accessible via browser or CLI. This enables developers to fine-tune, train, and deploy AI models with minimal friction and maximum flexibility.
    Starting Price: $0.04 per hour
  • 19
    fal

    fal

    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
  • 20
    Nebius

    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
  • 21
    Modal

    Modal

    Modal Labs

    We built a container system from scratch in rust for the fastest cold-start times. Scale to hundreds of GPUs and back down to zero in seconds, and pay only for what you use. Deploy functions to the cloud in seconds, with custom container images and hardware requirements. Never write a single line of YAML. Startups and academic researchers can get up to $25k free compute credits on Modal. These credits can be used towards GPU compute and accessing in-demand GPU types. Modal measures the CPU utilization continuously in terms of the number of fractional physical cores, each physical core is equivalent to 2 vCPUs. Memory consumption is measured continuously. For both memory and CPU, you only pay for what you actually use, and nothing more.
    Starting Price: $0.192 per core per hour
  • 22
    Ori GPU Cloud
    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
  • 23
    Instill Core

    Instill Core

    Instill AI

    Instill Core is an all-in-one AI infrastructure tool for data, model, and pipeline orchestration, streamlining the creation of AI-first applications. Access is easy via Instill Cloud or by self-hosting from the instill-core GitHub repository. Instill Core includes: Instill VDP: The Versatile Data Pipeline (VDP), designed for unstructured data ETL challenges, providing robust pipeline orchestration. Instill Model: An MLOps/LLMOps platform that ensures seamless model serving, fine-tuning, and monitoring for optimal performance with unstructured data ETL. Instill Artifact: Facilitates data orchestration for unified unstructured data representation. Instill Core simplifies the development and management of sophisticated AI workflows, making it indispensable for developers and data scientists leveraging AI technologies.
    Starting Price: $19/month/user
  • 24
    Featherless

    Featherless

    Featherless

    Featherless is an AI model provider that offers our subscribers access to a continually expanding library of Hugging Face models. With hundreds of new models daily, you need dedicated tools to keep up with the hype. No matter your use case, find and use the state-of-the-art AI model with Featherless. At present, we support LLaMA-3-based models, including LLaMA-3 and QWEN-2. Note that QWEN-2 models are only supported up to 16,000 context length. We plan to add more architectures to our supported list soon. We continuously onboard new models as they become available on Hugging Face. As we grow, we aim to automate this process to encompass all publicly available Hugging Face models with compatible architecture. To ensure fair individual account use, concurrent requests are limited according to the plan you've selected. Output is delivered at a speed of 10-40 tokens per second, depending on the model and prompt size.
    Starting Price: $10 per month
  • 25
    IBM watsonx.ai
    Now available—a next generation enterprise studio for AI builders to train, validate, tune and deploy AI models IBM® watsonx.ai™ AI studio is part of the IBM watsonx™ AI and data platform, bringing together new generative AI (gen AI) capabilities powered by foundation models and traditional machine learning (ML) into a powerful studio spanning the AI lifecycle. Tune and guide models with your enterprise data to meet your needs with easy-to-use tools for building and refining performant prompts. With watsonx.ai, you can build AI applications in a fraction of the time and with a fraction of the data. Watsonx.ai offers: End-to-end AI governance: Enterprises can scale and accelerate the impact of AI with trusted data across the business, using data wherever it resides. Hybrid, multi-cloud deployments: IBM provides the flexibility to integrate and deploy your AI workloads into your hybrid-cloud stack of choice.
  • 26
    Qubrid AI

    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
  • 27
    Substrate

    Substrate

    Substrate

    Substrate is the platform for agentic AI. Elegant abstractions and high-performance components, optimized models, vector database, code interpreter, and model router. Substrate is the only compute engine designed to run multi-step AI workloads. Describe your task by connecting components and let Substrate run it as fast as possible. We analyze your workload as a directed acyclic graph and optimize the graph, for example, merging nodes that can be run in a batch. The Substrate inference engine automatically schedules your workflow graph with optimized parallelism, reducing the complexity of chaining multiple inference APIs. No more async programming, just connect nodes and let Substrate parallelize your workload. Our infrastructure guarantees your entire workload runs in the same cluster, often on the same machine. You won’t spend fractions of a second per task on unnecessary data roundtrips and cross-region HTTP transport.
    Starting Price: $30 per month
  • 28
    NetMind AI

    NetMind AI

    NetMind AI

    NetMind.AI is a decentralized computing platform and AI ecosystem designed to accelerate global AI innovation. By leveraging idle GPU resources worldwide, it offers accessible and affordable AI computing power to individuals, businesses, and organizations of all sizes. The platform provides a range of services, including GPU rental, serverless inference, and an AI ecosystem that encompasses data processing, model training, inference, and agent development. Users can rent GPUs at competitive prices, deploy models effortlessly with on-demand serverless inference, and access a wide array of open-source AI model APIs with high-throughput, low-latency performance. NetMind.AI also enables contributors to add their idle GPUs to the network, earning NetMind Tokens (NMT) as rewards. These tokens facilitate transactions on the platform, allowing users to pay for services such as training, fine-tuning, inference, and GPU rentals.
  • 29
    Civo

    Civo

    Civo

    Civo is a cloud-native platform designed to simplify cloud computing for developers and businesses, offering fast, predictable, and scalable infrastructure. It provides managed Kubernetes clusters with industry-leading launch times of around 90 seconds, enabling users to deploy and scale applications efficiently. Civo’s offering includes enterprise-class compute instances, managed databases, object storage, load balancers, and cloud GPUs powered by NVIDIA A100 for AI and machine learning workloads. Their billing model is transparent and usage-based, allowing customers to pay only for the resources they consume with no hidden fees. Civo also emphasizes sustainability with carbon-neutral GPU options. The platform is trusted by industry-leading companies and offers a robust developer experience through easy-to-use dashboards, APIs, and educational resources.
    Starting Price: $250 per month
  • 30
    Amazon EC2 Trn1 Instances
    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