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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.

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
Groq logo
Groq
✓ verifiedFreemium

Fast, low-cost AI inference provider running LLMs on custom LPU chips via GroqCloud's pay-as-you-go API.

3.6M visits/mo
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
Evolink AI Model API logo
Evolink AI Model API
✓ verifiedPaid

One API to access leading LLM, image, video, and audio models with pay-as-you-go, usage-based pricing.

363K visits/mo1.5K 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
Pricing
Essential: $13.95/mo (+$12 credit)
Advanced: $26.95/mo (+$25 credit)
GPU hardware: from $0.29/hr

Free trial available

GPT-OSS 20B: $0.075 per 1M input tokens ($0.30 per 1M output)
GPT-OSS 120B: $0.15 per 1M input tokens

No public pricing

Usage-based pay-as-you-go (e.g., Seedance 2.0 $0.198/s, GPT Image 2 from $0.015/image)
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

Core features
  • 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
  • LPU custom inference hardware
  • GroqCloud tokens-as-a-service API
  • High-speed, low-latency inference
  • Pay-as-you-go token pricing
  • Free API key to start
  • Broad open-model support
  • 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
  • Single API for LLM, image, video, and audio models
  • Access to GPT, Claude, Gemini, Seedance, and more
  • Usage-based, pay-as-you-go pricing
  • Model comparison and documented capabilities
  • Smart Router for model selection
  • 99.9% uptime, no credit card to start
  • 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
Use cases
  • Running ComfyUI/Stable Diffusion without a local GPU
  • Training custom LoRA models
  • Face swapping and voice conversion
  • Generating images, video, and audio at scale
  • Running LLM inference at high speed
  • Cutting inference costs at scale
  • Powering low-latency AI chat apps
  • Serving models via a hosted API
  • 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
  • Add multiple AI models to a product via one API
  • Switch between model providers without rewrites
  • Generate video, images, and audio programmatically
  • Build AI agents and workflows
  • 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
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