Helicone vs Langfuse
Detailed side-by-side comparison to help you choose the right tool
Helicone
🔴DeveloperAI observability
open-source LLM observability and gateway platform
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Starting Price
FreeLangfuse
🔴DeveloperOpen-source LLM observability
open-source LLM observability, tracing, prompt and eval platform
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FreeFeature Comparison
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💡 Our Take
Choose Helicone if your priority is cost analytics, caching, and rate limiting with a 5-minute proxy setup that requires no SDK installation. Choose Langfuse if you need deep multi-step agent tracing, prompt management, and evaluation workflows with parent-child span hierarchies. Many teams use both — Helicone at the gateway for cost controls, Langfuse via SDK for tracing depth.
Helicone - Pros & Cons
Pros
- ✓Open-source positioning and one-line integration reduce adoption friction
- ✓Pricing is more transparent than many LLM observability tools
- ✓Combines observability and gateway controls in one product
Cons
- ✗Hobby plan limits retention to 7 days and ingestion to 10 logs/min
- ✗Advanced compliance and Slack support start at the $799/month Team tier
- ✗Teams needing deep eval workflows may still compare against Braintrust or Langfuse
Langfuse - Pros & Cons
Pros
- ✓Open-source and self-hostable, which is valuable for teams that do not want observability locked fully in a SaaS.
- ✓Clear fit for prompt lifecycle management: versioning, fetching, traces, datasets, and evals in one workflow.
- ✓MCP support is useful for coding agents that need to inspect or update observability assets safely.
- ✓Cloud pricing starts low enough for serious prototypes while still offering enterprise controls.
Cons
- ✗Unit-based pricing requires teams to understand how traces and observations translate into monthly spend.
- ✗Self-hosting reduces vendor lock-in but adds ClickHouse/database operations and upgrade responsibility.
- ✗Not a full application monitoring suite; you still need product analytics and infrastructure observability.
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