Langfuse vs Respan: Observability, Prompts & Evals Comparison
Compare Langfuse and Respan side by side. Both are tools in the Observability, Prompts & Evals category.
Updated February 28, 2026
The short answer
Choose Langfuse if fully open-source with MIT license and free for commercial use with no usage limits.
Choose Respan if unified observability across all LLM providers in one dashboard.
Want to compare Langfuse and Respan on your own traffic?
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 250+ models through one gateway. Free tier covers 10K traces per month. Setup in 5 minutes, no credit card.
Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | Open Source | — |
| Best For | Teams who want open-source LLM observability they can self-host and customize | — |
| Website | langfuse.com | respan.ai |
| Key Features |
| — |
| Use Cases |
| — |
Pros & Cons: Langfuse vs Respan
- +Fully open-source with MIT license and free for commercial use with no usage limits
- +Acquired by ClickHouse in January 2026, providing strong backing and future investment
- +Active development with strong community support and comprehensive documentation
- +Transparent pricing model based on units rather than complex metric calculations
- +Deep integrations with major frameworks like LangChain, OpenAI, and LlamaIndex
- −Recent acquisition by ClickHouse may lead to platform changes and strategic shifts
- −Smaller team of 7 employees may impact support capacity
- −Enterprise pricing at $3,450-$5,700/month can be expensive for mid-sized teams
- +Unified observability across all LLM providers in one dashboard
- +Real-time alerting for cost spikes, latency, and quality issues
- +Built-in evaluation tools for automated quality scoring
- +Prompt management with versioning and A/B testing
- +Easy integration with popular AI frameworks
- −Newer platform building out integrations with more frameworks
- −Advanced evaluation features require configuration effort
- −Smaller community compared to established observability tools
Pricing: Langfuse vs Respan
- · 10,000 traces/month
- · 7-day retention
- · Basic dashboards
- · Community support
- · 100,000 traces/month
- · 30-day retention
- · Advanced analytics
- · Priority support
- · Unlimited traces
- · Custom retention
- · SSO and RBAC
- · Dedicated support
When to Choose Langfuse vs Respan
- Self-hosted LLM monitoring
- Open-source tracing for AI applications
- Prompt versioning and management
About Langfuse
Langfuse is an open-source LLM engineering platform that provides comprehensive tools for traces, evaluations, prompt management, and metrics to debug and improve LLM applications. Founded in Berlin, Germany in 2022, Langfuse quickly became a leading platform in the LLM observability space. The platform features MIT-licensed open-source core with no usage limits for commercial use, making it highly accessible to teams of all sizes. Langfuse offers deep integration with popular frameworks including LangChain, OpenAI, LlamaIndex, and LiteLLM. The platform provides detailed tracing capabilities, evaluation tools, comprehensive prompt management, and rich metrics tracking. In January 2026, Langfuse was acquired by ClickHouse, Inc., marking a significant transatlantic venture exit and validating the platform's technology and market position. The acquisition demonstrates the value of Langfuse's approach to LLM observability, evaluations, and prompt management.
About Respan
Respan Observability provides comprehensive LLM monitoring and debugging for AI applications in production. The platform tracks every prompt, completion, latency metric, cost, and quality signal across all LLM providers from a single dashboard, giving engineering teams full visibility into their AI stack.
The observability suite includes real-time tracing of LLM calls with detailed breakdowns of token usage, response times, and error rates. Teams can set up alerts for cost spikes, latency degradation, or quality drops, and drill into individual traces to debug issues. Built-in evaluation tools enable automated quality scoring of LLM outputs using custom rubrics or reference-based evaluation.
Prompt management features allow teams to version, test, and deploy prompts without code changes. A/B testing capabilities enable comparing model performance across different configurations, and semantic caching identifies repeated queries to reduce costs. The platform integrates with popular frameworks like LangChain, LlamaIndex, and the Vercel AI SDK.
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.
Browse all Observability, Prompts & Evalstools →Other Observability, Prompts & Evals Tools
More Observability, Prompts & Evals Comparisons
Run Observability, Prompts & Evals in production with Respan
One platform for routing, observability, tracing, and evals across every LLM provider.