Langfuse vs Manus
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 | Manus |
|---|---|---|
| Our score | 89 | 82 |
| Pricing | Open-source self-hosted core plus commercial/cloud options depending on deployment path. | Free tier with limited task credits. Starter plan around $39/month for higher concurrency and usage limits. Professional plan around $199/month with team collaboration and priority execution. Enterprise pricing available on request. |
| 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 | Knowledge workers who need a reliable autonomous agent for research and data gathering, Founders and solo operators automating repetitive multi-step workflows, Analysts who need an agent to pull data, process it, and produce reports, Developers building on top of an existing production-grade agentic framework, Teams evaluating autonomous AI agents for enterprise deployment |
| Platforms | web, linux, api | web, desktop |
| API | Yes | No |
| Languages | en | en, zh |
| Pros |
|
|
| Cons |
|
|
| 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
Manus
82
- Pricing
- Free tier with limited task credits. Starter plan around $39/month for higher concurrency and usage limits. Professional plan around $199/month with team collaboration and priority execution. Enterprise pricing available on request.
- Free plan
- Yes
- Best for
- Knowledge workers who need a reliable autonomous agent for research and data gathering, Founders and solo operators automating repetitive multi-step workflows, Analysts who need an agent to pull data, process it, and produce reports, Developers building on top of an existing production-grade agentic framework, Teams evaluating autonomous AI agents for enterprise deployment
- Platforms
- web, desktop
- API
- No
- Languages
- en, zh
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
82Choose Manus if:
- You are Knowledge workers who need a reliable autonomous agent for research and data gathering
- You are Founders and solo operators automating repetitive multi-step workflows
- You are Analysts who need an agent to pull data, process it, and produce reports
- You want to start free
FAQ
- What is the difference between Langfuse and Manus?
- Langfuse is an open-source observability and prompt-management platform for llm applications, with tracing, datasets, and evaluation support. Manus is manus is a fully autonomous ai agent that plans and executes multi-step tasks end-to-end: browsing the web, writing and running code, analyzing data, managing files, and completing complex workflows without continuous human input.
- Which is cheaper, Langfuse or Manus?
- Langfuse: Open-source self-hosted core plus commercial/cloud options depending on deployment path.. Manus: Free tier with limited task credits. Starter plan around $39/month for higher concurrency and usage limits. Professional plan around $199/month with team collaboration and priority execution. Enterprise pricing available on request.. Langfuse has a free plan. Manus 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 Manus best for?
- Manus is best for Knowledge workers who need a reliable autonomous agent for research and data gathering, Founders and solo operators automating repetitive multi-step workflows, Analysts who need an agent to pull data, process it, and produce reports, Developers building on top of an existing production-grade agentic framework, Teams evaluating autonomous AI agents for enterprise deployment.