Alternatives to Deep Infra
Compare Deep Infra alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Deep Infra in 2026. Compare features, ratings, user reviews, pricing, and more from Deep Infra competitors and alternatives in order to make an informed decision for your business.
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Gemini Enterprise Agent Platform is a comprehensive solution from Google Cloud designed to help organizations build, scale, govern, and optimize AI agents. It represents the evolution of Vertex AI, combining advanced model development with new capabilities for agent orchestration and integration. The platform provides access to over 200 leading AI models, including Google’s Gemini series and third-party options like Anthropic’s Claude. It enables teams to create intelligent agents using both low-code and code-first development environments. With features like Agent Runtime and Memory Bank, businesses can deploy long-running agents that retain context and perform complex workflows. The platform emphasizes security and governance through tools like Agent Identity, Agent Registry, and Agent Gateway. It also includes optimization tools such as simulation, evaluation, and observability to ensure consistent agent performance.
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RunPod
RunPod
RunPod offers a cloud-based platform designed for running AI workloads, focusing on providing scalable, on-demand GPU resources to accelerate machine learning (ML) model training and inference. With its diverse selection of powerful GPUs like the NVIDIA A100, RTX 3090, and H100, RunPod supports a wide range of AI applications, from deep learning to data processing. The platform is designed to minimize startup time, providing near-instant access to GPU pods, and ensures scalability with autoscaling capabilities for real-time AI model deployment. RunPod also offers serverless functionality, job queuing, and real-time analytics, making it an ideal solution for businesses needing flexible, cost-effective GPU resources without the hassle of managing infrastructure. -
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OpenRouter
OpenRouter
OpenRouter is a unified interface for LLMs. OpenRouter scouts for the lowest prices and best latencies/throughputs across dozens of providers, and lets you choose how to prioritize them. No need to change your code when switching between models or providers. You can even let users choose and pay for their own. Evals are flawed; instead, compare models by how often they're used for different purposes. Chat with multiple at once in the chatroom. Model usage can be paid by users, developers, or both, and may shift in availability. You can also fetch models, prices, and limits via API. OpenRouter routes requests to the best available providers for your model, given your preferences. By default, requests are load-balanced across the top providers to maximize uptime, but you can customize how this works using the provider object in the request body. Prioritize providers that have not seen significant outages in the last 10 seconds.Starting Price: Free -
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SambaNova
SambaNova Systems
SambaNova is the leading purpose-built AI system for generative and agentic AI implementations, from chips to models, that gives enterprises full control over their model and private data. We take the best models, optimize them for fast tokens and higher batch sizes, the largest inputs and enable customizations to deliver value with simplicity. The full suite includes the SambaNova DataScale system, the SambaStudio software, and the innovative SambaNova Composition of Experts (CoE) model architecture. These components combine into a powerful platform that delivers unparalleled performance, ease of use, accuracy, data privacy, and the ability to power every use case across the world's largest organizations. We give our customers the optionality to experience through the cloud or on-premise. -
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CentML
CentML
CentML accelerates Machine Learning workloads by optimizing models to utilize hardware accelerators, like GPUs or TPUs, more efficiently and without affecting model accuracy. Our technology boosts training and inference speed, lowers compute costs, increases your AI-powered product margins, and boosts your engineering team's productivity. Software is no better than the team who built it. Our team is stacked with world-class machine learning and system researchers and engineers. Focus on your AI products and let our technology take care of optimum performance and lower cost for you. -
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Together AI
Together AI
Together AI provides an AI-native cloud platform built to accelerate training, fine-tuning, and inference on high-performance GPU clusters. Engineered for massive scale, the platform supports workloads that process trillions of tokens without performance drops. Together AI delivers industry-leading cost efficiency by optimizing hardware, scheduling, and inference techniques, lowering total cost of ownership for demanding AI workloads. With deep research expertise, the company brings cutting-edge models, hardware, and runtime innovations—like ATLAS runtime-learning accelerators—directly into production environments. Its full-stack ecosystem includes a model library, inference APIs, fine-tuning capabilities, pre-training support, and instant GPU clusters. Designed for AI-native teams, Together AI helps organizations build and deploy advanced applications faster and more affordably.Starting Price: $0.0001 per 1k tokens -
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Amazon SageMaker makes it easy to deploy ML models to make predictions (also known as inference) at the best price-performance for any use case. It provides a broad selection of ML infrastructure and model deployment options to help meet all your ML inference needs. It is a fully managed service and integrates with MLOps tools, so you can scale your model deployment, reduce inference costs, manage models more effectively in production, and reduce operational burden. From low latency (a few milliseconds) and high throughput (hundreds of thousands of requests per second) to long-running inference for use cases such as natural language processing and computer vision, you can use Amazon SageMaker for all your inference needs.
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Replicate
Replicate
Replicate is a platform that enables developers and businesses to run, fine-tune, and deploy machine learning models at scale with minimal effort. It offers an easy-to-use API that allows users to generate images, videos, speech, music, and text using thousands of community-contributed models. Users can fine-tune existing models with their own data to create custom versions tailored to specific tasks. Replicate supports deploying custom models using its open-source tool Cog, which handles packaging, API generation, and scalable cloud deployment. The platform automatically scales compute resources based on demand, charging users only for the compute time they consume. With robust logging, monitoring, and a large model library, Replicate aims to simplify the complexities of production ML infrastructure.Starting Price: Free -
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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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Simplismart
Simplismart
Fine-tune and deploy AI models with Simplismart's fastest inference engine. Integrate with AWS/Azure/GCP and many more cloud providers for simple, scalable, cost-effective deployment. Import open source models from popular online repositories or deploy your own custom model. Leverage your own cloud resources or let Simplismart host your model. With Simplismart, you can go far beyond AI model deployment. You can train, deploy, and observe any ML model and realize increased inference speeds at lower costs. Import any dataset and fine-tune open-source or custom models rapidly. Run multiple training experiments in parallel efficiently to speed up your workflow. Deploy any model on our endpoints or your own VPC/premise and see greater performance at lower costs. Streamlined and intuitive deployment is now a reality. Monitor GPU utilization and all your node clusters in one dashboard. Detect any resource constraints and model inefficiencies on the go. -
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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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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 -
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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
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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. -
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kluster.ai
kluster.ai
Kluster.ai is a developer-centric AI cloud platform designed to deploy, scale, and fine-tune large language models (LLMs) with speed and efficiency. Built for developers by developers, it offers Adaptive Inference, a flexible and scalable service that adjusts seamlessly to workload demands, ensuring high-performance processing and consistent turnaround times. Adaptive Inference provides three distinct processing options: real-time inference for ultra-low latency needs, asynchronous inference for cost-effective handling of flexible timing tasks, and batch inference for efficient processing of high-volume, bulk tasks. It supports a range of open-weight, cutting-edge multimodal models for chat, vision, code, and more, including Meta's Llama 4 Maverick and Scout, Qwen3-235B-A22B, DeepSeek-R1, and Gemma 3 . Kluster.ai's OpenAI-compatible API allows developers to integrate these models into their applications seamlessly.Starting Price: $0.15per input -
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Groq
Groq
GroqCloud is a high-performance AI inference platform built specifically for developers who need speed, scale, and predictable costs. It delivers ultra-fast responses for leading generative AI models across text, audio, and vision workloads. Powered by Groq’s purpose-built LPU (Language Processing Unit), the platform is designed for inference from the ground up, not adapted from training hardware. GroqCloud supports popular LLMs, speech-to-text, text-to-speech, and image-to-text models through industry-standard APIs. Developers can start for free and scale seamlessly as usage grows, with clear usage-based pricing. The platform is available in public, private, or co-cloud deployments to match different security and performance needs. GroqCloud combines consistent low latency with enterprise-grade reliability. -
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Fireworks AI
Fireworks AI
Fireworks partners with the world's leading generative AI researchers to serve the best models, at the fastest speeds. Independently benchmarked to have the top speed of all inference providers. Use powerful models curated by Fireworks or our in-house trained multi-modal and function-calling models. Fireworks is the 2nd most used open-source model provider and also generates over 1M images/day. Our OpenAI-compatible API makes it easy to start building with Fireworks. Get dedicated deployments for your models to ensure uptime and speed. Fireworks is proudly compliant with HIPAA and SOC2 and offers secure VPC and VPN connectivity. Meet your needs with data privacy - own your data and your models. Serverless models are hosted by Fireworks, there's no need to configure hardware or deploy models. Fireworks.ai is a lightning-fast inference platform that helps you serve generative AI models.Starting Price: $0.20 per 1M tokens -
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FriendliAI
FriendliAI
FriendliAI is a generative AI infrastructure platform that offers fast, efficient, and reliable inference solutions for production environments. It provides a suite of tools and services designed to optimize the deployment and serving of large language models (LLMs) and other generative AI workloads at scale. Key offerings include Friendli Endpoints, which allow users to build and serve custom generative AI models, saving GPU costs and accelerating AI inference. It supports seamless integration with popular open source models from the Hugging Face Hub, enabling lightning-fast, high-performance inference. FriendliAI's cutting-edge technologies, such as Iteration Batching, Friendli DNN Library, Friendli TCache, and Native Quantization, contribute to significant cost savings (50–90%), reduced GPU requirements (6× fewer GPUs), higher throughput (10.7×), and lower latency (6.2×).Starting Price: $5.9 per hour -
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DeepInfra
DeepInfra
DeepInfra is an AI inference cloud that makes it simple to run the latest machine learning models at scale, including LLMs, vision models, embeddings, image generation, video generation, speech, and more. It provides serverless inference through simple APIs, allowing developers to integrate production-ready AI models without managing GPU infrastructure, autoscaling, deployment complexity, or model hosting operations. DeepInfra supports OpenAI-compatible APIs for LLMs and embeddings, making it easier to switch from existing OpenAI-style integrations while accessing a broad catalog of open and commercial models. Its Native API gives access to every model type available on the platform, including image generation, speech recognition, object detection, token classification, fill-mask, image classification, zero-shot image classification, and text classification. DeepInfra is optimized for scalable, low-latency inference and runs models on high-performance GPU infrastructure.Starting Price: $1.98 per hour -
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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 -
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Wallaroo.AI
Wallaroo.AI
Wallaroo facilitates the last-mile of your machine learning journey, getting ML into your production environment to impact the bottom line, with incredible speed and efficiency. Wallaroo is purpose-built from the ground up to be the easy way to deploy and manage ML in production, unlike Apache Spark, or heavy-weight containers. ML with up to 80% lower cost and easily scale to more data, more models, more complex models. Wallaroo is designed to enable data scientists to quickly and easily deploy their ML models against live data, whether to testing environments, staging, or prod. Wallaroo supports the largest set of machine learning training frameworks possible. You’re free to focus on developing and iterating on your models while letting the platform take care of deployment and inference at speed and scale. -
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Atlas Cloud
Atlas Cloud
Atlas Cloud is a full-modal AI inference platform built for developers who want to run every type of AI model through a single API. It supports chat, reasoning, image, audio, and video inference without requiring multiple providers. Developers can discover, test, and scale over 300 production-ready models from leading AI ecosystems in one unified workspace. Atlas Cloud simplifies experimentation with an interactive playground and one-click model customization. Its infrastructure is designed for high performance, low latency, and production stability at scale. With serverless access, agent solutions, and GPU cloud options, it adapts to different development and deployment needs. Atlas Cloud helps teams build and ship AI-powered applications faster and more efficiently. -
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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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Hugging Face
Hugging Face
Hugging Face is a leading platform for AI and machine learning, offering a vast hub for models, datasets, and tools for natural language processing (NLP) and beyond. The platform supports a wide range of applications, from text, image, and audio to 3D data analysis. Hugging Face fosters collaboration among researchers, developers, and companies by providing open-source tools like Transformers, Diffusers, and Tokenizers. It enables users to build, share, and access pre-trained models, accelerating AI development for a variety of industries.Starting Price: $9 per month -
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Amazon EC2 Inf1 Instances
Amazon
Amazon EC2 Inf1 instances are purpose-built to deliver high-performance and cost-effective machine learning inference. They provide up to 2.3 times higher throughput and up to 70% lower cost per inference compared to other Amazon EC2 instances. Powered by up to 16 AWS Inferentia chips, ML inference accelerators designed by AWS, Inf1 instances also feature 2nd generation Intel Xeon Scalable processors and offer up to 100 Gbps networking bandwidth to support large-scale ML applications. These instances are ideal for deploying applications such as search engines, recommendation systems, computer vision, speech recognition, natural language processing, personalization, and fraud detection. Developers can deploy their ML models on Inf1 instances using the AWS Neuron SDK, which integrates with popular ML frameworks like TensorFlow, PyTorch, and Apache MXNet, allowing for seamless migration with minimal code changes.Starting Price: $0.228 per hour -
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KServe
KServe
Highly scalable and standards-based model inference platform on Kubernetes for trusted AI. KServe is a standard model inference platform on Kubernetes, built for highly scalable use cases. Provides performant, standardized inference protocol across ML frameworks. Support modern serverless inference workload with autoscaling including a scale to zero on GPU. Provides high scalability, density packing, and intelligent routing using ModelMesh. Simple and pluggable production serving for production ML serving including prediction, pre/post-processing, monitoring, and explainability. Advanced deployments with the canary rollout, experiments, ensembles, and transformers. ModelMesh is designed for high-scale, high-density, and frequently-changing model use cases. ModelMesh intelligently loads and unloads AI models to and from memory to strike an intelligent trade-off between responsiveness to users and computational footprint.Starting Price: Free -
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Cerebras
Cerebras
We’ve built the fastest AI accelerator, based on the largest processor in the industry, and made it easy to use. With Cerebras, blazing fast training, ultra low latency inference, and record-breaking time-to-solution enable you to achieve your most ambitious AI goals. How ambitious? We make it not just possible, but easy to continuously train language models with billions or even trillions of parameters – with near-perfect scaling from a single CS-2 system to massive Cerebras Wafer-Scale Clusters such as Andromeda, one of the largest AI supercomputers ever built. -
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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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GMI Cloud
GMI Cloud
GMI Cloud provides a complete platform for building scalable AI solutions with enterprise-grade GPU access and rapid model deployment. Its Inference Engine offers ultra-low-latency performance optimized for real-time AI predictions across a wide range of applications. Developers can deploy models in minutes without relying on DevOps, reducing friction in the development lifecycle. The platform also includes a Cluster Engine for streamlined container management, virtualization, and GPU orchestration. Users can access high-performance GPUs, InfiniBand networking, and secure, globally scalable infrastructure. Paired with popular open-source models like DeepSeek R1 and Llama 3.3, GMI Cloud delivers a powerful foundation for training, inference, and production AI workloads.Starting Price: $2.50 per hour -
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Baseten
Baseten
Baseten is a high-performance platform designed for mission-critical AI inference workloads. It supports serving open-source, custom, and fine-tuned AI models on infrastructure built specifically for production scale. Users can deploy models on Baseten’s cloud, their own cloud, or in a hybrid setup, ensuring flexibility and scalability. The platform offers inference-optimized infrastructure that enables fast training and seamless developer workflows. Baseten also provides specialized performance optimizations tailored for generative AI applications such as image generation, transcription, text-to-speech, and large language models. With 99.99% uptime, low latency, and support from forward deployed engineers, Baseten aims to help teams bring AI products to market quickly and reliably.Starting Price: Free -
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AWS EC2 Trn3 Instances
Amazon
Amazon EC2 Trn3 UltraServers are AWS’s newest accelerated computing instances, powered by the in-house Trainium3 AI chips and engineered specifically for high-performance deep-learning training and inference workloads. These UltraServers are offered in two configurations, a “Gen1” with 64 Trainium3 chips and a “Gen2” with up to 144 Trainium3 chips per UltraServer. The Gen2 configuration delivers up to 362 petaFLOPS of dense MXFP8 compute, 20 TB of HBM memory, and a staggering 706 TB/s of aggregate memory bandwidth, making it one of the highest-throughput AI compute platforms available. Interconnects between chips are handled by a new “NeuronSwitch-v1” fabric to support all-to-all communication patterns, which are especially important for large models, mixture-of-experts architectures, or large-scale distributed training. -
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Qualcomm AI Inference Suite
Qualcomm
The Qualcomm AI Inference Suite is a comprehensive software platform designed to streamline the deployment of AI models and applications across cloud and on-premises environments. It offers seamless one-click deployment, allowing users to easily integrate their own models, including generative AI, computer vision, and natural language processing, and build custom applications using common frameworks. The suite supports a wide range of AI use cases such as chatbots, AI agents, retrieval-augmented generation (RAG), summarization, image generation, real-time translation, transcription, and code development. Powered by Qualcomm Cloud AI accelerators, it ensures top performance and cost efficiency through embedded optimization techniques and state-of-the-art models. It is designed with high availability and strict data privacy in mind, ensuring that model inputs and outputs are not stored, thus providing enterprise-grade security. -
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SquareFactory
SquareFactory
End-to-end project, model and hosting management platform, which allows companies to convert data and algorithms into holistic, execution-ready AI-strategies. Build, train and manage models securely with ease. Create products that consume AI models from anywhere, any time. Minimize risks of AI investments, while increasing strategic flexibility. Completely automated model testing, evaluation deployment, scaling and hardware load balancing. From real-time, low-latency, high-throughput inference to batch, long-running inference. Pay-per-second-of-use model, with an SLA, and full governance, monitoring and auditing tools. Intuitive interface that acts as a unified hub for managing projects, creating and visualizing datasets, and training models via collaborative and reproducible workflows. -
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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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Lambda
Lambda.ai
Lambda provides high-performance supercomputing infrastructure built specifically for training and deploying advanced AI systems at massive scale. Its Superintelligence Cloud integrates high-density power, liquid cooling, and state-of-the-art NVIDIA GPUs to deliver peak performance for demanding AI workloads. Teams can spin up individual GPU instances, deploy production-ready clusters, or operate full superclusters designed for secure, single-tenant use. Lambda’s architecture emphasizes security and reliability with shared-nothing designs, hardware-level isolation, and SOC 2 Type II compliance. Developers gain access to the world’s most advanced GPUs, including NVIDIA GB300 NVL72, HGX B300, HGX B200, and H200 systems. Whether testing prototypes or training frontier-scale models, Lambda offers the compute foundation required for superintelligence-level performance. -
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Intel Tiber AI Cloud
Intel
Intel® Tiber™ AI Cloud is a powerful platform designed to scale AI workloads with advanced computing resources. It offers specialized AI processors, such as the Intel Gaudi AI Processor and Max Series GPUs, to accelerate model training, inference, and deployment. Optimized for enterprise-level AI use cases, this cloud solution enables developers to build and fine-tune models with support for popular libraries like PyTorch. With flexible deployment options, secure private cloud solutions, and expert support, Intel Tiber™ ensures seamless integration, fast deployment, and enhanced model performance.Starting Price: Free -
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Azure OpenAI Service
Microsoft
Apply advanced coding and language models to a variety of use cases. Leverage large-scale, generative AI models with deep understandings of language and code to enable new reasoning and comprehension capabilities for building cutting-edge applications. Apply these coding and language models to a variety of use cases, such as writing assistance, code generation, and reasoning over data. Detect and mitigate harmful use with built-in responsible AI and access enterprise-grade Azure security. Gain access to generative models that have been pretrained with trillions of words. Apply them to new scenarios including language, code, reasoning, inferencing, and comprehension. Customize generative models with labeled data for your specific scenario using a simple REST API. Fine-tune your model's hyperparameters to increase accuracy of outputs. Use the few-shot learning capability to provide the API with examples and achieve more relevant results.Starting Price: $0.0004 per 1000 tokens -
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Snowflake
Snowflake
Snowflake is a comprehensive AI Data Cloud platform designed to eliminate data silos and simplify data architectures, enabling organizations to get more value from their data. The platform offers interoperable storage that provides near-infinite scale and access to diverse data sources, both inside and outside Snowflake. Its elastic compute engine delivers high performance for any number of users, workloads, and data volumes with seamless scalability. Snowflake’s Cortex AI accelerates enterprise AI by providing secure access to leading large language models (LLMs) and data chat services. The platform’s cloud services automate complex resource management, ensuring reliability and cost efficiency. Trusted by over 11,000 global customers across industries, Snowflake helps businesses collaborate on data, build data applications, and maintain a competitive edge.Starting Price: $2/credit -
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NVIDIA Picasso
NVIDIA
NVIDIA Picasso is a cloud service for building generative AI–powered visual applications. Enterprises, software creators, and service providers can run inference on their models, train NVIDIA Edify foundation models on proprietary data, or start from pre-trained models to generate image, video, and 3D content from text prompts. Picasso service is fully optimized for GPUs and streamlines training, optimization, and inference on NVIDIA DGX Cloud. Organizations and developers can train NVIDIA’s Edify models on their proprietary data or get started with models pre-trained with our premier partners. Expert denoising network to generate photorealistic 4K images. Temporal layers and novel video denoiser generate high-fidelity videos with temporal consistency. A novel optimization framework for generating 3D objects and meshes with high-quality geometry. Cloud service for building and deploying generative AI-powered image, video, and 3D applications. -
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Seldon
Seldon Technologies
Deploy machine learning models at scale with more accuracy. Turn R&D into ROI with more models into production at scale, faster, with increased accuracy. Seldon reduces time-to-value so models can get to work faster. Scale with confidence and minimize risk through interpretable results and transparent model performance. Seldon Deploy reduces the time to production by providing production grade inference servers optimized for popular ML framework or custom language wrappers to fit your use cases. Seldon Core Enterprise provides access to cutting-edge, globally tested and trusted open source MLOps software with the reassurance of enterprise-level support. Seldon Core Enterprise is for organizations requiring: - Coverage across any number of ML models deployed plus unlimited users - Additional assurances for models in staging and production - Confidence that their ML model deployments are supported and protected. -
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Anyscale
Anyscale
Anyscale is a unified AI platform built around Ray, the world’s leading AI compute engine, designed to help teams build, deploy, and scale AI and Python applications efficiently. The platform offers RayTurbo, an optimized version of Ray that delivers up to 4.5x faster data workloads, 6.1x cost savings on large language model inference, and up to 90% lower costs through elastic training and spot instances. Anyscale provides a seamless developer experience with integrated tools like VSCode and Jupyter, automated dependency management, and expert-built app templates. Deployment options are flexible, supporting public clouds, on-premises clusters, and Kubernetes environments. Anyscale Jobs and Services enable reliable production-grade batch processing and scalable web services with features like job queuing, retries, observability, and zero-downtime upgrades. Security and compliance are ensured with private data environments, auditing, access controls, and SOC 2 Type II attestation.Starting Price: $0.00006 per minute -
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NVIDIA NIM
NVIDIA
Explore the latest optimized AI models, connect AI agents to data with NVIDIA NeMo, and deploy anywhere with NVIDIA NIM microservices. NVIDIA NIM is a set of easy-to-use inference microservices that facilitate the deployment of foundation models across any cloud or data center, ensuring data security and streamlined AI integration. Additionally, NVIDIA AI provides access to the Deep Learning Institute (DLI), offering technical training to gain in-demand skills, hands-on experience, and expert knowledge in AI, data science, and accelerated computing. AI models generate responses and outputs based on complex algorithms and machine learning techniques, and those responses or outputs may be inaccurate, harmful, biased, or indecent. By testing this model, you assume the risk of any harm caused by any response or output of the model. Please do not upload any confidential information or personal data unless expressly permitted. Your use is logged for security purposes. -
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Canopy Wave
Canopy Wave
Canopy Wave is the best inference platform for open models, built to deliver high-quality, reliable, and secure AI services from infrastructure to build, tune, and scale AI models. Its model platform gives users instant access to advanced open source models optimized for quality, speed, and security through API, with a model library covering different types and fields, so users can call models directly without additional development or adaptation. Canopy Wave’s serverless inference service lets teams run pretrained models through simple API calls without managing infrastructure, with fast response, low latency, no cold start issues, and globally optimized performance powered by next-generation GPUs and edge caching. For production workloads that need stronger control, dedicated endpoints run inference at scale with exceptional speed and reliability on hardware instances dedicated exclusively to the user.Starting Price: $0.07 per GB per month -
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Radiant
Radiant
Radiant is a fully integrated AI infrastructure platform designed to deliver end-to-end capabilities for building and scaling AI systems. It combines compute, software, energy, and capital into a unified ecosystem, enabling organizations to move from concept to deployment efficiently. Radiant’s AI Cloud includes NVIDIA-accelerated computing along with MLOps tools such as inference, fine-tuning, model registry, and serverless Kubernetes. Its proprietary software platform supports intelligent scheduling, automated node management, and secure multi-tenancy for large-scale operations. With infrastructure designed to scale from thousands to over 100,000 GPUs, Radiant ensures consistent performance and operational control. The platform also integrates energy solutions through its powered-land portfolio, optimizing costs and sustainability. Backed by significant capital resources, Radiant can support large-scale AI initiatives globally.Starting Price: $3.24 per month -
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Amazon SageMaker Feature Store is a fully managed, purpose-built repository to store, share, and manage features for machine learning (ML) models. Features are inputs to ML models used during training and inference. For example, in an application that recommends a music playlist, features could include song ratings, listening duration, and listener demographics. Features are used repeatedly by multiple teams and feature quality is critical to ensure a highly accurate model. Also, when features used to train models offline in batch are made available for real-time inference, it’s hard to keep the two feature stores synchronized. SageMaker Feature Store provides a secured and unified store for feature use across the ML lifecycle. Store, share, and manage ML model features for training and inference to promote feature reuse across ML applications. Ingest features from any data source including streaming and batch such as application logs, service logs, clickstreams, sensors, etc.
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Accelerate your deep learning workload. Speed your time to value with AI model training and inference. With advancements in compute, algorithm and data access, enterprises are adopting deep learning more widely to extract and scale insight through speech recognition, natural language processing and image classification. Deep learning can interpret text, images, audio and video at scale, generating patterns for recommendation engines, sentiment analysis, financial risk modeling and anomaly detection. High computational power has been required to process neural networks due to the number of layers and the volumes of data to train the networks. Furthermore, businesses are struggling to show results from deep learning experiments implemented in silos.
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Modular
Modular
Modular is a unified AI inference platform designed to run models efficiently across diverse hardware environments. It enables developers to deploy and scale AI workloads on GPUs, CPUs, and ASICs using a single, integrated stack. The platform optimizes performance from low-level GPU kernels to high-level API endpoints. Modular supports both managed cloud deployments and self-hosted environments, offering flexibility for different use cases. It allows users to run open-source or custom models with high performance and cost efficiency. With features like hardware portability and dynamic scaling, it reduces vendor lock-in and infrastructure complexity. By combining performance optimization and deployment simplicity, Modular helps teams build and run AI applications at scale. -
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Striveworks Chariot
Striveworks
Make AI a trusted part of your business. Build better, deploy faster, and audit easily with the flexibility of a cloud-native platform and the power to deploy anywhere. Easily import models and search cataloged models from across your organization. Save time by annotating data rapidly with model-in-the-loop hinting. Understand the full provenance of your data, models, workflows, and inferences. Deploy models where you need them, including for edge and IoT use cases. Getting valuable insights from your data is not just for data scientists. With Chariot’s low-code interface, meaningful collaboration can take place across teams. Train models rapidly using your organization's production data. Deploy models with one click and monitor models in production at scale. -
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Wafer
Wafer
Wafer delivers the fastest open source LLMs for enterprise through serverless and dedicated inference built for production AI workloads. Its serverless inference gives teams access to top open models with no infrastructure, no deployment overhead, and fast APIs, including GLM-5.2-Fast for low-latency inference with EAGLE speculative decoding and a per-stream throughput SLA, GLM-5.2 as a flagship model with stronger coding and reasoning capabilities, and more. Wafer’s technology uses agents that optimize inference across the stack, identifying and enhancing bottlenecks in orchestration, algorithms, serving engines, GPU kernels, and diverse hardware. It profiles the stack to see whether latency or throughput comes from scheduling, decoding, kernels, memory pressure, or hardware fit, then tries many paths and ships the measured winner. Instead of relying on a single switch or heuristic, Wafer searches model, engine, kernel, and hardware combinations.Starting Price: Free -
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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
