GPU hosting made understandable

Find the right GPU cloud for what you actually want to run.

Compare GPU providers for AI video, image generation, LLMs and training — without decoding enterprise cloud jargon.

✓ Retail-friendly✓ Indie developer focused✓ Clear hosting types
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GPU hosting providers

Filter by what you want to run, rather than by infrastructure terminology.

CUDO Compute

Enterprise GPU infrastructure and cluster operations for AI workloads.

Best forTraining / fine-tuning
GPU rangeSee provider
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Hyperstack

GPU virtual machines with API access for AI training, inference and rendering.

Pods / VMs
Best forTraining / fine-tuning
GPU rangeSee provider
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Jarvislabs

GPU virtual machines, development templates and serverless deployments for AI workloads.

Pods / VMsServerless
Best forLLM inference, Training / fine-tuning, Experimenting and testing
GPU rangeSee provider
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TensorDock

GPU cloud virtual machines for deep learning, AI and rendering, with deployment APIs.

Pods / VMs
Best forTraining / fine-tuning
GPU rangeSee provider
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Thunder Compute

GPU instances and sandboxes for AI development, evaluations and post-training.

Pods / VMs
Best forTraining / fine-tuning, Experimenting and testing
GPU rangeSee provider
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fal

Image, video and audio model APIs, serverless GPUs and dedicated compute for model development.

Pods / VMsServerlessAPI
Best forAI video generation, AI image generation, Bursty production API, Training / fine-tuning
GPU rangeSee provider
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Lambda

On-demand GPU instances and clusters for model training and inference, with API and CLI access.

Pods / VMsUp to 180.00 GB VRAM
Best forLLM inference, Training / fine-tuning
GPU rangeNVIDIA A10, NVIDIA A100 PCIe, NVIDIA A100 SXM, NVIDIA B200 SXM6, NVIDIA GH200, NVIDIA H100 PCIe, NVIDIA H100 SXM5, NVIDIA Quadro RTX 6000, NVIDIA RTX A6000

Modal

Serverless GPU compute for model inference, fine-tuning, training and evaluation.

ServerlessUp to 180.00 GB VRAM
Best forAI video generation, AI image generation, LLM inference, Bursty production API, Training / fine-tuning, Experimenting and testing
GPU rangeNVIDIA A100 40 GB, NVIDIA A100 80 GB, NVIDIA B200 SXM6, NVIDIA H100 SXM5, NVIDIA H200 SXM, NVIDIA L40S

Paperspace / DigitalOcean

DigitalOcean Paperspace provides GPU virtual machines with published machine configurations.

Pods / VMsUp to 80.00 GB VRAM
Best forTraining / fine-tuning
GPU rangeNVIDIA A100 40 GB, NVIDIA A100 80 GB, NVIDIA H100, NVIDIA RTX A4000, NVIDIA RTX A5000, NVIDIA RTX A6000

Replicate

Hosted APIs for image, video and language models, with fine-tuning and custom deployments.

API
Best forAI video generation, AI image generation, LLM inference, Bursty production API, Training / fine-tuning
GPU rangeSee provider
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RunPod

GPU Pods for container workloads alongside serverless inference and deployment APIs.

Pods / VMsServerlessUp to 180.00 GB VRAM
Best forTraining / fine-tuning, Experimenting and testing
GPU rangeNVIDIA A100 PCIe, NVIDIA B200 SXM6, NVIDIA H100 PCIe, NVIDIA H100 SXM5, NVIDIA H200 SXM, NVIDIA L40S, NVIDIA RTX 4090, NVIDIA RTX A5000
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Together AI

Hosted model inference, fine-tuning and GPU compute for AI development.

API
Best forLLM inference, Bursty production API, Training / fine-tuning, Experimenting and testing
GPU rangeSee provider
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Vast.ai

Marketplace GPU containers for training, inference and development, plus serverless deployments.

Pods / VMsServerless
Best forTraining / fine-tuning, Experimenting and testing
GPU rangeSee provider
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Verda

Verda provides GPU instances and serverless containers for training and inference.

Pods / VMsServerless
Best forLLM inference, Training / fine-tuning
GPU rangeSee provider
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CloudRift

GPU rentals using virtual machines, containers and bare metal, plus hosted inference endpoints.

Pods / VMsAPI
Best forLLM inference, Bursty production API, Training / fine-tuning
GPU rangeSee provider
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CoreWeave

GPU infrastructure with managed Kubernetes for training and inference.

Best forTraining / fine-tuning
GPU rangeSee provider
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Fluidstack

Large-scale AI compute and data-center infrastructure for enterprise workloads.

Best forTraining / fine-tuning
GPU rangeSee provider
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Gcore

GPU virtual machines and bare metal for AI training, inference and accelerated computing.

Pods / VMs
Best forTraining / fine-tuning
GPU rangeSee provider
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io.net

Distributed GPU infrastructure accessed through IO Cloud.

Best forTraining / fine-tuning, Experimenting and testing
GPU rangeSee provider
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Latitude.sh

Dedicated bare-metal GPU infrastructure for machine-learning workloads.

Pods / VMs
Best forTraining / fine-tuning
GPU rangeSee provider
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Nebius

AI cloud infrastructure for model training and inference, including hosted model services.

Best forLLM inference, Training / fine-tuning
GPU rangeSee provider
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OVHcloud

Public-cloud GPU instances and AI services for training and inference.

Pods / VMsAPI
Best forBursty production API, Training / fine-tuning
GPU rangeSee provider
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Radiant / Ori

Radiant's GPU infrastructure includes virtual machines and bare-metal compute.

Pods / VMs
Best forTraining / fine-tuning
GPU rangeSee provider
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Scaleway

GPU instances for AI development, model training and inference.

Pods / VMs
Best forTraining / fine-tuning
GPU rangeSee provider
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Voltage Park

Bare-metal GPU clusters for large-scale AI training.

Pods / VMs
Best forTraining / fine-tuning
GPU rangeSee provider
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Vultr

GPU virtual machines for AI, machine learning and accelerated computing.

Pods / VMs
Best forTraining / fine-tuning
GPU rangeSee provider
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Amazon Web Services

Amazon EC2 offers GPU virtual machines for machine learning and accelerated computing.

Pods / VMs
Best forTraining / fine-tuning
GPU rangeSee provider
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Google Cloud

Compute Engine provides GPU-backed virtual machines with configurable machine types.

Pods / VMs
Best forTraining / fine-tuning
GPU rangeSee provider
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Microsoft Azure

Azure provides GPU virtual machines for AI and high-performance computing.

Pods / VMs
Best forTraining / fine-tuning
GPU rangeSee provider
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Oracle Cloud

GPU virtual machines and bare-metal instances for AI training and accelerated computing.

Pods / VMs
Best forTraining / fine-tuning
GPU rangeSee provider
Check provider pricing
Simple decision

Pod or serverless?

For most people, this is the first decision that matters.

▣

GPU Pod / VM

A GPU machine stays allocated to you while it is running.

  • Best for steady or continuous work
  • Predictable environment
  • You pay while the machine is running
  • Concurrent jobs usually need your own queue/workers
Choose this when your GPU is busy often.
⚡

Serverless GPU

Workers spin up for jobs and scale with demand.

  • Best for bursts and unpredictable traffic
  • Multiple requests can scale across workers
  • You mainly pay for execution time
  • Cold starts can matter
Choose this when requests arrive in bursts.
Quick calculator

What does one generation actually cost?

Hourly rates are hard to compare. Convert them into an approximate cost per image, video or inference job.

Cost per job = hourly GPU price × job seconds ÷ 3,600
Approx. cost / job$0.049
Approx. monthly compute$48.63
Compute only. Storage, idle time, cold starts, data transfer and provider-specific charges may change the total.
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