Langfuse and Helicone serve as observability tools for LLM applications, offering comprehensive monitoring and analytics. Langfuse boasts a higher GitHub star count at 24,100 and substantial npm downloads of 870,710/week, compared to Helicone's 5,406 stars and 10 downloads/week. Helicone, however, maintains a stronger user satisfaction with average ratings of 4.5/5 from G2 reviews.
Best for
Helicone is the better choice when user satisfaction and straightforward pricing options, including a free tier, are prioritized, along with more focus on educational projects and resource optimization.
Best for
Langfuse is the better choice when a team needs deep analytics and a broad set of integrations for debugging and tracking LLM applications, supported by a strong development community.
Key Differences
Verdict
Langfuse should be chosen by teams needing extensive observability features and a robust community. Helicone is ideal for those prioritizing initial affordability and greater user satisfaction. Engineering leaders should consider team size, budget, and specific use case requirements when choosing between the two tools.
Helicone
AI Gateway & LLM Observability
Helicone appears to be well-regarded, achieving positive ratings of 4/5 and 5/5 on G2, indicating user satisfaction with its functionality. Users highlight its integration within the domain of LLM (Large Language Model) tools, although it seems to have its own tracing format, which may add complexity in environments where standardization, like OpenTelemetry, is present. While pricing specifics are not detailed, the overall sentiment regarding value appears to be positive, given the high ratings. Helicone has a solid reputation, with notable mentions across multiple platforms, suggesting a strong presence and interest in its capabilities.
Langfuse
Traces, evals, prompt management and metrics to debug and improve your LLM application.
Langfuse is recognized for its capability to effectively track LLM calls, providing visibility into AI operations which is crucial for production environments. However, some users have raised concerns about its lack of understanding of agent topology and potential interoperability limitations with other tracing formats. There isn't much specific sentiment mentioned about pricing, but there seems to be an implication that it's a paid solution compared to some open-source alternatives. Overall, Langfuse is appreciated as a valuable tool for observability in AI, though it faces some competition from both paid and open-source tools offering varied features.
Helicone
-50% vs last weekLangfuse
+100% vs last weekHelicone
Langfuse
Helicone
Langfuse
Helicone
Pricing found: $79, $799, $5, $100
Langfuse
Pricing found: $29 / month, $8/100k, $199 / month, $8/100k, $300/mo
Helicone (9)
Langfuse (8)
Only in Helicone (1)
Only in Langfuse (1)
Shared (12)
Only in Helicone (7)
Only in Langfuse (3)
Helicone
What do you like best about Helicone?Track usage, costs, and latency metrics with one line of codes. Review collected by and hosted on G2.com.What do you dislike about Helicone?How long it takes to scan the computer while doing the upload. Review collected by and hosted on G2.com.
What do you like best about Helicone?It's actually a great Open-source and cheap Platform for tracking different LLM usage, and can also create alerts on LLM responses. It supports multiple LLMs, including open-source ones. You'll get 100,000 free token uses. It's easy to implement and also offers great customer support. I use it more to integrate it into my projects. Review collected by and hosted on G2.com.What do you dislike about Helicone?The issue is that there are numerous alternatives, and implementing a custom LLM proxy on a framework like Axflow is challenging. The Experiment features are yet to be introduced, so we'll have to wait and see how go it is. Review collected by and hosted on G2.com.
Langfuse
No reviews yet
Helicone
Langfuse
Helicone
Langfuse
Helicone
No YouTube channel
Langfuse
Langfuse Context: All things MCP with Adam Jones (Tech Lead at Anthropic)
Jan 6, 2026
Continuous Evaluation, Monitoring, and Operations of AI Agents with AWS Bedrock AgentCore & Langfuse
Nov 25, 2025
Collect User Feedback of your LLM Agent in Langfuse
Nov 14, 2025
Langfuse Launch Week Day 6: Dataset Schema Enforcement & Folders
Nov 8, 2025
Helicone
Langfuse
Helicone
Langfuse
Helicone
OpenTelemetry just standardized LLM tracing. Here's what it actually looks like in code.
Every LLM tool invents its own tracing format. Langfuse has one. Helicone has one. Arize has one. If...
Langfuse
OpenTelemetry just standardized LLM tracing. Here's what it actually looks like in code.
Every LLM tool invents its own tracing format. Langfuse has one. Helicone has one. Arize has one. If...
Shared (3)
Only in Langfuse (2)
For detailed tracking and debugging of LLM workflows, Langfuse is better; for educational or cost-aware projects, Helicone may be more appropriate.
Langfuse's pricing starts at $29/month with a tiered structure, while Helicone offers a freemium model and subscription options starting at $5.
Langfuse likely has better community support given its higher GitHub star count and more npm downloads.
While possible, using both may complicate setups due to potential differences in tracing formats and interoperability challenges.
Helicone may be easier to start with due to its free tier and higher user satisfaction ratings, facilitating initial testing and adoption.
