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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.

Deep Infra logo
Deep Infra
✓ verifiedPaid

Low-cost inference cloud with developer APIs to run open ML models and on-demand GPUs, billed pay-per-use.

375K visits/mo
WaveSpeedAI logo
WaveSpeedAI
✓ verifiedFree trial

Pay-per-use API hub aggregating 1000+ image, video, and audio generation models for developers building AI media pipelines.

2.2M 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
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
Vast ai logo
Vast ai
✓ verifiedPaid

GPU rental marketplace with per-second billing across thousands of GPUs, aimed at AI training, inference, and fine-tuning workloads.

1.4M visits/mo
Pricing

No public pricing

Silver: $100 top-up (higher rate limits)
Gold: $1,000 top-up (higher rate limits)
Ultra: $10,000 top-up (highest rate limits)

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
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

No public pricing

Core features
  • Hosted inference for many open models
  • Simple REST/OpenAI-compatible API
  • Pay-per-token or per-time billing
  • On-demand GPU rental
  • Broad catalog (Llama, DeepSeek, Qwen, Flux, etc.)
  • DeepStart and DeepCluster tooling
  • Unified API access to 1000+ image/video/audio generation models
  • Pay-per-use pricing billed per image or per second of video
  • Includes chat/LLM model access (Claude, GPT, Gemini, etc.) priced per token
  • Account tiers unlock higher GPU limits and concurrency
  • CLI and desktop app for building workflows
  • Enterprise options with dedicated support and custom deployment
  • 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%
  • 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
  • On-demand GPU cloud with per-second billing
  • Interruptible instances at discounted rates for batch/fault-tolerant jobs
  • Reserved capacity with 1, 3, or 6-month terms for steady workloads
  • Serverless deployment with autoscale-to-zero for inference endpoints
  • Dedicated multi-node clusters with InfiniBand for large-scale training
  • Python SDK and CLI plus REST API for programmatic provisioning
  • Access to 68+ GPU types across 40+ data centers
  • Pre-configured templates for popular open-source models
Use cases
  • Serving open-source models via API
  • Building AI apps cost-efficiently
  • Renting GPUs for inference or training
  • Scaling inference up and down on demand
  • Integrating AI image/video generation into an app via API
  • Building automated content pipelines needing multiple AI models
  • Testing and comparing many generative models from one account
  • Scaling AI media production with volume-based account tiers
  • Accessing both media-generation and LLM APIs from one platform
  • Train large AI/ML models on GPU clusters
  • Run scalable inference workloads
  • Store and manage large training datasets
  • Run Slurm/Kubernetes AI pipelines
  • 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
  • ML engineers training or fine-tuning models on rented GPUs
  • Startups running inference at scale without owning hardware
  • Developers needing quick, low-cost access to specific GPU types
  • Teams building AI agents that autonomously provision compute
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