Langfuse vs Google Opal
A side-by-side comparison to help you choose the right tool.
89
Langfuse scores higher overall (89/100)
But the best choice depends on your specific needs. Compare below.
| Feature | Langfuse | Google Opal |
|---|---|---|
| Our score | 89 | 78 |
| Pricing | Open-source self-hosted core plus commercial/cloud options depending on deployment path. | Public/preview positioning with pricing not clearly separated as a standalone commercial plan. |
| Free plan | Yes | Yes |
| Best for | Teams shipping LLM apps in production, Developers who need traces and evaluation workflows, Organizations standardizing prompt and experiment tracking | Ops and business teams prototyping AI workflows quickly, Builders who want something lighter than full code, Teams exploring shareable AI task flows |
| Platforms | web, linux, api | web |
| API | Yes | Yes |
| Languages | en | en |
| Pros |
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| Visit site | Visit site |
Langfuse
89
- Pricing
- Open-source self-hosted core plus commercial/cloud options depending on deployment path.
- Free plan
- Yes
- Best for
- Teams shipping LLM apps in production, Developers who need traces and evaluation workflows, Organizations standardizing prompt and experiment tracking
- Platforms
- web, linux, api
- API
- Yes
- Languages
- en
- Pricing
- Public/preview positioning with pricing not clearly separated as a standalone commercial plan.
- Free plan
- Yes
- Best for
- Ops and business teams prototyping AI workflows quickly, Builders who want something lighter than full code, Teams exploring shareable AI task flows
- Platforms
- web
- API
- Yes
- Languages
- en
89Choose Langfuse if:
- You are Teams shipping LLM apps in production
- You are Developers who need traces and evaluation workflows
- You are Organizations standardizing prompt and experiment tracking
- You want to start free
78Choose Google Opal if:
- You are Ops and business teams prototyping AI workflows quickly
- You are Builders who want something lighter than full code
- You are Teams exploring shareable AI task flows
- You want to start free
FAQ
- What is the difference between Langfuse and Google Opal?
- Langfuse is an open-source observability and prompt-management platform for llm applications, with tracing, datasets, and evaluation support. Google Opal is google's no-code or low-code ai workflow builder for chaining prompts, models, and tools into shareable mini-app style flows.
- Which is cheaper, Langfuse or Google Opal?
- Langfuse: Open-source self-hosted core plus commercial/cloud options depending on deployment path.. Google Opal: Public/preview positioning with pricing not clearly separated as a standalone commercial plan.. Langfuse has a free plan. Google Opal has a free plan.
- Who is Langfuse best for?
- Langfuse is best for Teams shipping LLM apps in production, Developers who need traces and evaluation workflows, Organizations standardizing prompt and experiment tracking.
- Who is Google Opal best for?
- Google Opal is best for Ops and business teams prototyping AI workflows quickly, Builders who want something lighter than full code, Teams exploring shareable AI task flows.