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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.

218K 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
Coze logo
Coze
✓ verifiedFreemium

ByteDance's Coze (Kouzi): an all-in-one AI office assistant for writing, slides, sheets, design, podcasts and images.

7.2M 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

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

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
  • LLM API router
  • OpenAI API proxy
  • Model aggregation (OpenAI, Gemini, DeepSeek, Llama, Qwen, Claude, etc.)
  • Unified OpenAI API standard
  • Unlimited concurrency
  • 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
  • AI writing
  • AI presentation/PPT generation
  • AI spreadsheets and tables
  • AI design
  • AI podcast generation
  • AI image generation
  • 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
  • Integrating multiple AI models into applications using a single API
  • Accessing the latest AI models through a unified interface
  • Managing and scaling AI model usage with unlimited concurrency
  • Running LLM inference at high speed
  • Cutting inference costs at scale
  • Powering low-latency AI chat apps
  • Serving models via a hosted API
  • Drafting documents
  • Building presentations
  • Generating spreadsheets
  • Creating designs and images
  • Producing podcasts
  • Turning prompts into maintainable, spec-matched code
  • Catching bugs unit tests miss
  • Reviewing PRs and fixing bugs in CI/CD
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