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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.

Arize AI logo
Arize AI
✓ verifiedFreemium

AI observability and evaluation platform to trace, evaluate and improve LLM agents in production, with an open-source Phoenix core.

248K visits/mo
27K 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
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
Pricing
AX Free: $0/mo (25k spans/mo)
AX Pro: $50/mo (50k spans/mo)

No public 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
Core features
  • Agent and LLM tracing
  • Large-scale evaluations
  • Open-source Phoenix observability
  • Alyx AI engineering agent
  • OpenTelemetry-based instrumentation
  • Experiments and prompt playgrounds
  • Open-Source AI Gateway
  • Multi-LLM Management & Cost Optimization
  • Efficient and Secure LLMs Invocation
  • Unified API Signature for LLMs
  • Load Balancer for seamless switching between LLMs
  • Fine-Grained Traffic Control for LLMs
  • LLM Quota Management
  • Real-time LLM Traffic Monitoring
  • Caching Strategies for AI in Production
  • Flexible Prompt Management
  • AI writing
  • AI presentation/PPT generation
  • AI spreadsheets and tables
  • AI design
  • AI podcast generation
  • AI image generation
  • 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
Use cases
  • Debugging AI agents in production
  • Measuring LLM output quality
  • Catching regressions before deploy
  • Building API portals for secure sharing of internal APIs with partners.
  • Tracking API usage and driving API monetization.
  • Managing and securing API access in compliance with enterprise policies.
  • Connecting to multiple AI large models simultaneously.
  • Optimizing LLM costs and improving efficiency.
  • Protecting against LLM attacks and data leaks.
  • Drafting documents
  • Building presentations
  • Generating spreadsheets
  • Creating designs and images
  • Producing podcasts
  • Running LLM inference at high speed
  • Cutting inference costs at scale
  • Powering low-latency AI chat apps
  • Serving models via a hosted API
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