Langfuse vs Portkey: Observability, Prompts & Evals Comparison
Compare Langfuse and Portkey side by side. Both are tools in the Observability, Prompts & Evals category.
Updated March 10, 2026
The short answer
Choose Langfuse if fully open-source with MIT license and free for commercial use with no usage limits.
Choose Portkey if enterprise-scale monitoring (10B requests/month).
Want to compare Langfuse and Portkey 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 | portkey.ai |
| Key Features |
| — |
| Use Cases |
| — |
Pros & Cons: Langfuse vs Portkey
- +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
- +Enterprise-scale monitoring (10B requests/month)
- +Sub-40ms overhead
- +Comprehensive analytics and tracing
- +Strong security certifications
- −Professional tier expensive (USD 2-5k/mo)
- −Open-source has limited features
- −Complex for small teams
Pricing: Langfuse vs Portkey
- · Open-source
- · Basic observability
- · Self-managed
- · Community support
- · Managed service
- · Advanced analytics
- · Standard support
- · Team features
- · Custom limits
- · SOC2, ISO27001
- · Priority support
- · Private deployment
When to Choose Langfuse vs Portkey
- 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 Portkey
Portkey Observability is the monitoring and analytics component of the Portkey AI platform, providing comprehensive visibility into LLM applications. The platform tracks requests, costs, latency, errors, and user behavior across all LLM providers. Portkey Observability integrates seamlessly with the Portkey AI Gateway, offering unified monitoring for multi-provider AI applications. The platform provides real-time dashboards, alerting, and detailed trace analysis to help teams optimize AI performance and costs. Portkey processes over 10 billion requests monthly with sub-40ms overhead, providing enterprise-grade observability for production AI systems.
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.