Langfuse and Helicone are both strong contenders in the observability space for LLM applications, with Langfuse boasting high npm downloads of 870,710 per week and a large community with 24,100 GitHub stars. Helicone, while smaller in scale with 5,406 GitHub stars, is highly rated with an average user rating of 4.5/5 from reviews. Langfuse provides comprehensive visibility into traces, while Helicone offers a more flexible pricing model with a freemium tier.
Best for
Langfuse is the better choice when deep visibility into traces and a larger community presence are priorities for teams dealing with complex LLM workflows.
Best for
Helicone is the better choice when affordability is key, especially for startups and educational projects, thanks to its freemium tier and solid user satisfaction ratings.
Key Differences
Verdict
Langfuse is ideal for teams requiring detailed observability features and those willing to pay for extensive integration capabilities, especially in larger LLM workflows. Helicone suits budget-conscious teams or educational projects due to its freemium model and solid usability ratings. Engineering leaders should balance the need for specific features against cost considerations when making a decision.
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
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
-50% vs last weekHelicone
-67% vs last weekLangfuse
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Pricing found: $29 / month, $8/100k, $199 / month, $8/100k, $300/mo
Helicone
Pricing found: $79, $799, $5, $100
Langfuse (8)
Helicone (9)
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Only in Helicone (1)
Shared (12)
Only in Langfuse (3)
Only in Helicone (7)
Langfuse
No reviews yet
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.
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Jan 6, 2026
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Nov 25, 2025
Collect User Feedback of your LLM Agent in Langfuse
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Langfuse Launch Week Day 6: Dataset Schema Enforcement & Folders
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Helicone
No YouTube channel
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Anyone actually built a real feedback loop for Claude agents in production? Because "run evals and pray" isn't cutting it
So I've been running a multi-agent setup with Claude for a few months now mostly customer-facing stuff, some internal tooling. And i keep hitting this problem that I think a lot of people here are probably dealing with too but nobody really talks about. You ship a prompt change. Or you swap from So
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...
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Langfuse is better for detailed LLM monitoring and debugging, while Helicone is ideal for budget-driven educational projects.
Langfuse uses subscription and tiered pricing, starting at $29/month, whereas Helicone offers both subscription and freemium options, starting at $79.
Langfuse likely has better community support given its 24,100 GitHub stars compared to Helicone's 5,406.
While technically feasible, attention needs to be paid to their different integration and compatibility features.
Helicone may be easier to start with, especially for small teams or individuals due to its freemium tier and fewer barriers to entry.
