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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

Runpod logo
Runpod
✓ verifiedPaid

Developer-focused GPU cloud offering on-demand pods, serverless inference and multi-node clusters at per-second pricing for AI workloads.

2.3M visits/mo
Replicate AI logo
Replicate AI
✓ verifiedPaid

Pay-per-use cloud API to run, fine-tune, and deploy thousands of open-source and proprietary AI models with one line of code.

1.3M visits/mo17K saves
Atlas Cloud logo
Atlas Cloud
✓ verifiedPaid

Unified pay-per-use API serving 400+ multimodal AI models (image, video, audio, 3D, LLM) through one OpenAI-compatible key.

958K visits/mo
MimicPC logo
MimicPC
✓ verifiedFreemium

Cloud platform to run open-source AI apps like ComfyUI and Stable Diffusion and train LoRAs on rented GPUs, billed hourly.

299K visits/mo
Nebius logo
Nebius
✓ verifiedPaid

AI-focused cloud offering NVIDIA GPU compute, storage and MLOps tooling for training and inference at scale, with usage-based pricing.

678K visits/mo133K saves
Pricing
Pods A40 48GB: $0.44/hr
Pods RTX 4090 24GB: $0.69/hr
Pods A100 SXM 80GB: $1.49/hr
Pods H100 SXM 80GB: $2.99/hr
Pods H200 141GB: $4.39/hr
Pods B300 288GB: $7.39/hr
CPU (Small): $0.000025/sec ($0.09/hr)
Nvidia A100 80GB: $0.0014/sec ($5.04/hr)
Nvidia H100: $0.001525/sec ($5.49/hr)

Free trial available

Seedance 2.0 video: from $0.09/sec
GPT Image 2: from $0.009/image
Nano Banana 2: from $0.04/image
Essential: $13.95/mo (+$12 credit)
Advanced: $26.95/mo (+$25 credit)
GPU hardware: from $0.29/hr

Free trial available

NVIDIA H100: $3.85/GPU-hour on-demand ($2.15 preemptible)
NVIDIA H200: $4.50/GPU-hour on-demand
NVIDIA B200: $7.15/GPU-hour on-demand
Shared filesystem storage: $0.08/GiB per month
Core features
  • On-demand GPU pods across 30+ GPU types and 31 regions
  • Serverless GPU endpoints with sub-200ms cold starts
  • Zero idle cost billing for inference workloads
  • Multi-node clusters for distributed training
  • Persistent network storage for full pipelines
  • Real-time logs, monitoring and autoscaling from 0 to hundreds of workers
  • One-line API calls to run community and proprietary AI models
  • Support for image, video, speech, and LLM generation models
  • Fine-tuning and custom model deployment via Cog
  • Per-second usage billing on shared or dedicated hardware
  • Automatic scaling for high-traffic private models
  • Thousands of community-published models with production APIs
  • 400+ AI models via one unified API
  • Multimodal coverage: image, video, audio, 3D, LLM
  • On-demand, pay-per-use pricing
  • Day-0 access to new state-of-the-art models
  • OpenAI-compatible single key
  • SOC 2 and HIPAA compliance, 99.99% uptime
  • Pre-installed open-source AI apps (ComfyUI, SD, Fooocus)
  • LoRA and custom model training
  • Image, video, audio, and LLM workflows
  • Hourly GPU rental across several tiers
  • Private storage and shareable workflows
  • No-deployment, browser-based access
  • NVIDIA GPU instances (H100, H200, B200, GB200)
  • On-demand and preemptible GPU pricing
  • High-performance and object storage
  • Managed Kubernetes and Slurm (Soperator)
  • Serverless and managed inference (Token Factory)
  • MLOps tooling and 24/7 expert support
  • Commitment discounts up to 35%
Use cases
  • Renting GPUs for model training and fine-tuning
  • Deploying low-latency real-time inference APIs
  • Running AI agents that need to scale instantly
  • Processing compute-heavy batch or distributed workloads
  • Developers embedding image/video/speech generation into an app via API
  • Teams deploying and scaling their own fine-tuned models
  • Builders comparing outputs from multiple AI models in one playground
  • Companies avoiding GPU infrastructure management for ML inference
  • Integrate video and image generation
  • Access many LLMs through one API
  • Build multimodal AI applications
  • Batch generate and prototype cheaply
  • Running ComfyUI/Stable Diffusion without a local GPU
  • Training custom LoRA models
  • Face swapping and voice conversion
  • Generating images, video, and audio at scale
  • Train large AI/ML models on GPU clusters
  • Run scalable inference workloads
  • Store and manage large training datasets
  • Run Slurm/Kubernetes AI pipelines
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