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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
MindStudio logo
MindStudio
✓ verifiedFreemium

No-code visual builder to create, deploy and orchestrate AI agents across 200+ models, for individuals to enterprise.

1.8M visits/mo
MiniMax M2.7 logo
MiniMax M2.7
✓ verifiedFreemium

MiniMax's general-purpose autonomous AI agent that plans and completes complex multi-step tasks from a single prompt.

1.1M 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
Pricing

No public pricing

Free: $0 + usage (1 agent, 1,000 runs/mo)
Individual: $20/mo + usage (unlimited agents and runs)

No public pricing

Starter: $0/mo + compute ($30 free credit)
Team: $250/mo + compute
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
  • No-code visual agent builder
  • 200+ AI models via service router
  • 100+ prebuilt templates
  • Agent skills, plugins and workflows
  • AI Media Workbench for video/image
  • Enterprise controls (SSO, permissions, self-host)
  • Autonomous multi-step task execution
  • Natural-language task delegation
  • Powered by MiniMax frontier models
  • Handles research, building and content tasks
  • 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
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
  • Automating business workflows
  • Building custom AI agents without code
  • Content and media generation
  • Deploying agents across a team or org
  • Delegating complex tasks to an AI agent
  • Automating research and analysis
  • Producing reports and deliverables
  • Deploying and scaling model inference
  • Fine-tuning and training models
  • Running batch/parallel AI jobs
  • Executing untrusted code in sandboxes
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