Langfuse vs Promptfoo

Langfuse is freemium — a usable free tier with paid plans above it. Promptfoo is freemium — a usable free tier with paid plans above it. Both are listed under LLM Eval & Observability, so this is a like-for-like comparison. Neither is ranked above the other — Flocci carries no sponsored placement.

Langfuse vs Promptfoo — straight answers

Langfuse vs Promptfoo: what is the difference?

Langfuse is freemium — a usable free tier with paid plans above it and is listed for fully open-source and self-hostable for free via Docker Compose/Kubernetes, not just a hosted SaaS. Promptfoo is freemium — a usable free tier with paid plans above it and is listed for open-source CLI/library for evaluating prompts, models and RAG pipelines side by side, runs in CI. Both sit in LLM Eval & Observability.

Is Langfuse or Promptfoo cheaper to start with?

Neither — Langfuse and Promptfoo are both freemium, so the choice comes down to capability rather than cost. Both entries list what they uniquely do above.

Which should I choose, Langfuse or Promptfoo?

Choose Langfuse if you need fully open-source and self-hostable for free via Docker Compose/Kubernetes, not just a hosted SaaS; choose Promptfoo if you need open-source CLI/library for evaluating prompts, models and RAG pipelines side by side, runs in CI. Flocci AI Tools does not rank one above the other — it shows both feature sets side by side and lets the requirement decide.

Langfuse compared with Promptfoo: pricing tier, category, listed capabilities and links.
 LangfusePromptfoo
Pricing tierFree tier + paid plansFree tier + paid plans
Free to startYesYes
CategoryAI Models & Local ExecutionAI Models & Local Execution
TypeLLM Eval & ObservabilityLLM Eval & Observability
Listed capabilities
  • Fully open-source and self-hostable for free via Docker Compose/Kubernetes, not just a hosted SaaS
  • Hobby cloud plan is free with no credit card, 50k observability units/month
  • Combines tracing, prompt management, evals and datasets in one open platform
  • Open-source CLI/library for evaluating prompts, models and RAG pipelines side by side, runs in CI
  • Automated red-teaming to surface prompt injection, jailbreak and data-leak vulnerabilities
  • 300,000+ user community with an enterprise tier for teams needing hosted guardrails
Tagslangfuse, llm observability, prompt management, tracing, open source, free, evaluationpromptfoo, prompt testing, llm red teaming, eval framework, open source, free, ci for prompts
Websitelangfuse.compromptfoo.dev
Full pageLangfuse details →Promptfoo details →
AlternativesLangfuse alternatives →Promptfoo alternatives →

Arize Phoenix

LLM Eval & Observability
free
  • Fully open-source, self-hostable with zero setup via `uvx` (pip/conda also supported)
  • Combines tracing, evals, datasets, experiments and prompt playground in one local-first tool
  • AI engineering agent (PXI) built in for automated troubleshooting of traces

Google Stax

LLM Eval & Observability
freeNew
  • Build evals with human raters or LLM autoraters on your own data
  • Compare models and prompts on quality, latency and token cost
  • Prebuilt and custom evaluators

Laminar

LLM Eval & Observability
freeNew
  • Open-source observability and evals platform for AI agents (Apache-2.0)
  • Traces, session replay for browser agents and evaluations
  • Self-hostable

DeepEval

LLM Eval & Observability
freeNew
  • Open-source LLM evaluation framework with pytest-style tests and 50+ metrics
  • RAG, agent and conversational metrics; red-teaming module
  • Apache-2.0; optional Confident AI cloud has a free tier

EleutherAI LM Evaluation Harness

LLM Eval & Observability
freeNew
  • Standard open framework for running hundreds of benchmarks (MMLU, GSM8K and more) against any LLM
  • Backs the Hugging Face Open LLM evaluations
  • MIT licensed CLI and Python library

OpenLLMetry (Traceloop)

LLM Eval & Observability
freeNew
  • OpenTelemetry-based instrumentation for LLM calls, vector DBs and frameworks
  • Ships traces to Datadog, Grafana, Honeycomb or any OTel backend
  • Apache-2.0