Agenta vs Langfuse (2026)
Updated March 10, 2026
Overview
Agenta is an open-source platform for prompt engineering, evaluation, and experimentation. It provides a prompt playground, version control for prompts, A/B testing, and evaluation pipelines. Teams can iterate on prompts collaboratively, track experiments, and deploy optimized prompts to production.
Langfuse is an open-source LLM engineering platform for tracing, evals, and prompt management, self-hosted or on Langfuse Cloud with a free plan.
Key features
Core capabilities each platform advertises.
- Tracing for LLM calls, tool runs, and agent steps
- Python and TypeScript SDKs plus OpenTelemetry
- LLM-as-a-judge and custom evaluations
- Datasets and experiments
- Prompt management and playground
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Production-ready
- Good performance
- Active development
Cons
- Pricing varies
- Setup required
Pros
- MIT-licensed core, self-hostable with Docker Compose or Kubernetes
- Tracing, evals, and prompt management in one tool
- Unlimited users on paid cloud plans
- Free Hobby plan with 50k units a month
- Native SDKs plus OpenTelemetry for other languages
Cons
- No LLM gateway, so routing, failover, and spend limits need a separate tool
- Hobby plan keeps 30 days of data and caps at 2 users
- Enterprise SSO and RBAC need the $300/month Teams add-on on Pro
- Self-hosting means running and scaling Langfuse's services yourself
Agenta or Langfuse — which should you choose?
Choose Agenta if you wantChoose if you want
Choose Langfuse if you wantChoose if you want
- Tracing and debugging LLM apps and agents
- Self-hosting LLM observability
- Versioning prompts across environments
- Scoring outputs with LLM judges and human review
Compare Agenta and Langfuse on your own traffic
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