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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.

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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
Fiddler AI logo
Fiddler AI
✓ verifiedFreemium

Enterprise AI observability and security platform to monitor, evaluate, and govern agentic and ML systems with guardrails.

51K visits/mo
LLM Price Check logo
LLM Price Check
✓ verifiedFree

Free comparison tool for LLM API prices across providers, with a calculator to estimate token costs.

17K visits/mo
Pricing
Developer: $0 (10K events/month, up to 5 users, 30-day retention)
Free: $0 (real-time guardrails)
Developer: $0.002 per trace

No public pricing

Core features
  • 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
  • End-to-end agentic and ML observability
  • Real-time guardrails (hallucination, PII, jailbreak)
  • Continuous evaluations and custom judges
  • Root-cause analysis and decision lineage
  • AI governance, risk, and compliance controls
  • Flexible SaaS, VPC, or on-prem deployment
  • Compare LLM API prices across providers
  • Per-million-token input/output rates
  • Quality and context-window data
  • Token cost calculator
  • Sortable, searchable model table
Use cases
  • 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
  • Monitoring production AI agents
  • Enforcing safety guardrails on LLM apps
  • Evaluating and debugging model behavior
  • Governance and compliance for enterprise AI
  • Compare LLM API costs
  • Estimate token spending for a project
  • Pick a cost-effective model
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