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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
Openlayer logo
Openlayer
✓ verifiedFreemium

AI governance and observability platform with 100+ automated tests and real-time guardrails to evaluate and monitor ML/LLM systems.

24K visits/mo
honeyhive.ai logo
honeyhive.ai
✓ verifiedFreemium

Observability and evaluation platform for production LLM agents, built on OpenTelemetry for tracing, monitoring and testing.

24K visits/mo
SiliconFlow logo
SiliconFlow
✓ verified

Developer platform serving 200+ optimized LLMs via APIs; high traffic.

434K visits/mo1.1K saves
Pricing
AX Free: $0/mo (25k spans/mo)
AX Pro: $50/mo (50k spans/mo)
Basic: Free (20k inferences/mo, 1 member, 5 projects)
Developer: $0 (10K events/month, up to 5 users, 30-day retention)

No public pricing

Core features
  • Agent and LLM tracing
  • Large-scale evaluations
  • Open-source Phoenix observability
  • Alyx AI engineering agent
  • OpenTelemetry-based instrumentation
  • Experiments and prompt playgrounds
  • 100+ automated AI tests
  • Offline evaluation and CI/CD for AI
  • Real-time observability and tracing
  • Guardrails against PII leaks, injection, hallucination
  • Data-quality and drift monitoring
  • Compliance/governance alignment
  • Git, SDK, CLI and REST API integration
  • OpenTelemetry-native distributed tracing across 100+ LLMs and frameworks
  • Online evaluation via LLM-as-a-judge or code
  • Offline experiments and regression detection
  • Annotation queues for expert review
  • Alerts and drift detection
  • Prompt management, CLI and docs MCP server
  • Access over 200 optimized models, including LLMs, image, video, and audio processing.
  • Achieve low-latency, high-throughput inference with SiliconFlow's self-developed acceleration frameworks.
  • Deploy models via serverless inference, dedicated endpoints, or reserved GPUs to suit various workloads.
  • Customize models to your data with built-in monitoring and elastic compute resources.
  • Ensure data privacy and business security with dynamic scaling and fault tolerance mechanisms.
Use cases
  • Debugging AI agents in production
  • Measuring LLM output quality
  • Catching regressions before deploy
  • Evaluate models before production
  • Monitor live AI systems for issues
  • Prevent unsafe or non-compliant outputs
  • Catch data drift and quality problems
  • Debugging multi-agent systems
  • Monitoring live agent quality at scale
  • Catching regressions before release
  • Human review of edge cases
  • Aligning automated evaluators with domain experts
  • Quickly deploy various AI models via a simple API, supporting tasks like text, image, audio, and video processing.
  • Utilize serverless GPUs to automatically scale AI applications, ensuring flexibility and cost-efficiency.
  • Access high-performance GPUs for demanding workloads, such as large-scale inference and video generation.
  • Deploy custom models with guaranteed performance and scalability, tailored to specific business needs.
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