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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.

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
CometAPI logo
CometAPI
✓ verifiedPaid

Unified API to 500+ AI models (OpenAI, Anthropic, Google, etc.) with OpenAI-compatible calls priced ~20% below official rates.

363K visits/mo4.8K saves
MuAPI logo
MuAPI
✓ verifiedPaid

Unified pay-per-generation API for 500+ image, video and audio models like FLUX, Kling and Seedance at low cost.

411K visits/mo
Modal logo
Modal
✓ verifiedFreemium

Serverless AI cloud for running inference, training and sandboxes on GPUs with fast cold starts and pay-per-use billing.

988K visits/mo
Kiro AI logo
Kiro AI
✓ verifiedFreemium

Kiro is a spec-driven agentic coding tool for IDE, CLI and web that turns prompts into specs and catches bugs with property-based tests.

3.8M visits/mo
Pricing

No public pricing

Pay-as-you-go, min top-up $10
GPT-5.6: $4 / 1M tokens
Claude Sonnet 5: $1.6 / 1M tokens

Free trial available

No public pricing

Starter: $0/mo + compute ($30 free credit)
Team: $250/mo + compute
Free: $0/mo (50 credits)
Pro: $20/user/mo (1,000 credits)
Pro+: $40/user/mo (2,000 credits)
Pro Max: $100/user/mo (5,000 credits)
Power: $200/user/mo (10,000 credits)
Core features
  • 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
  • One key for 500+ models
  • OpenAI-compatible API
  • Pay-as-you-go credits (~20% below list)
  • Multimodal: text, image, video, audio
  • Usage analytics and budget alerts
  • Integrations (Claude Code, n8n, Zapier, etc.)
  • Single API for 500+ image, video and audio models
  • Pay-per-generation billing with no subscription
  • No charge on failed tasks
  • Workflows, agents and studio tools
  • MCP and CLI integrations, white-label option
  • Serverless GPU compute defined in Python
  • Sub-second container cold starts
  • Autoscale 0 to 1000+ GPUs
  • Inference, training and batch workloads
  • Secure sandboxes for untrusted code
  • Built-in logging and observability
  • Spec-driven development (requirements, design, tasks)
  • Parallel agents, local or cloud
  • Property-based and correctness testing
  • Works in IDE, CLI, web and mobile
  • Multiple models (Claude, open-weight, Auto)
  • Headless CLI for CI/CD
  • Context from tools like Figma and Terraform
Use cases
  • 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
  • Consolidating multi-provider AI billing
  • Switching models without re-integration
  • Powering apps and automation pipelines
  • Benchmarking models in one playground
  • Building apps on top of many generative models via one API
  • Generating images, video and audio at scale
  • Cutting model API costs versus direct providers
  • Deploying white-label AI generation studios
  • Deploying and scaling model inference
  • Fine-tuning and training models
  • Running batch/parallel AI jobs
  • Executing untrusted code in sandboxes
  • Turning prompts into maintainable, spec-matched code
  • Catching bugs unit tests miss
  • Reviewing PRs and fixing bugs in CI/CD
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