Langtrace vs Helicone
Detailed side-by-side comparison to help you choose the right tool
Langtrace
🔴DeveloperBusiness Analytics
Langtrace: Open-source observability platform for LLM applications and AI agents with OpenTelemetry-based tracing, cost tracking, and performance analytics.
Was this helpful?
Starting Price
FreeHelicone
🔴DeveloperBusiness Analytics
Open-source LLM observability platform and API gateway that provides cost analytics, request logging, caching, and rate limiting through a simple proxy-based integration requiring only a base URL change.
Was this helpful?
Starting Price
FreeFeature Comparison
Scroll horizontally to compare details.
Langtrace - Pros & Cons
Pros
- ✓Open-source with generous free tier and self-hosting options
- ✓Built on industry-standard OpenTelemetry for interoperability
- ✓Extensive integration support for LLM providers and frameworks
- ✓Real-time observability with detailed trace visualization
- ✓Complete data ownership with self-hosted deployment option
Cons
- ✗TypeScript SDK has limited framework support compared to Python
- ✗AGPL license may be restrictive for some commercial use cases
- ✗Self-hosted setup requires managing multiple services (Next.js, Postgres, ClickHouse)
- ✗Pricing model scales per-user which can become expensive for larger teams
- ✗Limited semantic conventions as standards are still evolving
Helicone - Pros & Cons
Pros
- ✓Proxy-based integration requires only a base URL change — genuinely zero-code setup for OpenAI and Anthropic users in under 5 minutes
- ✓Real-time cost analytics with per-user, per-feature, and per-model breakdowns are best-in-class for LLM spend management
- ✓Gateway-level request caching can reduce API costs 20-50% for applications with repetitive queries
- ✓Open-source under MIT license with self-hosted Docker option gives full data control for security-conscious teams
- ✓Built-in rate limiting and retry logic at the proxy layer eliminates operational code from your application
- ✓Free tier includes 10,000 requests/month with full feature access — generous compared to most observability platforms in our directory
Cons
- ✗Proxy architecture adds 20-50ms latency per request, which compounds in latency-sensitive agent loops with many sequential calls
- ✗Individual request-level visibility doesn't capture multi-step agent workflows or retrieval pipeline context natively
- ✗Session and trace grouping features are less mature than Langfuse or LangSmith's dedicated tracing capabilities
- ✗Free tier limited to 10,000 requests/month — production applications will quickly need the $20/seat/month Pro plan
- ✗Self-hosted deployment is operationally complex, requiring Supabase and ClickHouse infrastructure to run in production
Not sure which to pick?
🎯 Take our quiz →🔒 Security & Compliance Comparison
Scroll horizontally to compare details.
Price Drop Alerts
Get notified when AI tools lower their prices
Get weekly AI agent tool insights
Comparisons, new tool launches, and expert recommendations delivered to your inbox.