Keywords AI
Arize AI vs Langfuse
Compare Arize AI and Langfuse side by side. Both are tools in the Observability, Prompts & Evals category.
Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | Freemium | Open Source |
| Best For | ML teams who need comprehensive observability spanning traditional ML models and LLM applications | Teams who want open-source LLM observability they can self-host and customize |
| Website | arize.com | langfuse.com |
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When to Choose Arize AI vs Langfuse
- Production ML and LLM monitoring
- Embedding quality monitoring
- Model performance tracking
- Self-hosted LLM monitoring
- Open-source tracing for AI applications
- Prompt versioning and management
About Arize AI
Arize AI provides an ML and LLM observability platform for monitoring model performance in production. For LLM applications, Arize offers trace visualization, prompt analysis, embedding drift detection, and retrieval evaluation. Their open-source Phoenix library provides local tracing and evaluation. Arize helps teams identify quality issues, debug failures, and continuously improve AI system performance.
About Langfuse
Langfuse is an open-source LLM observability platform that provides tracing, analytics, prompt management, and evaluation for AI applications. It captures detailed traces of LLM calls, supports custom scoring, and integrates with LangChain, LlamaIndex, Vercel AI SDK, and raw API calls. Langfuse can be self-hosted for data privacy or used as a managed cloud service. Its open-source model and generous free tier make it popular with startups and developers.
What is Observability, Prompts & Evals?
Tools for monitoring LLM applications in production, managing and versioning prompts, and evaluating model outputs. Includes tracing, logging, cost tracking, prompt engineering platforms, automated evaluation frameworks, and human annotation workflows.
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