Langfuse vs Promptfoo

Side-by-side comparison of features, pricing, and ratings

Analysis reviewed Live tool data as of 2026-08-15
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At a glance

DimensionLangfusePromptfoo
PricingFree cloud tier + paid (self-host free via MIT)Free community (10k probes/mo) + Enterprise
Best ForProduction observability & prompt managementEnterprise security & red teaming
Key FeatureTraces, evals, prompt mgmt, experimentsAutomated red teaming, guardrails, CI/CD scanning
Self-HostingYes (MIT license)Yes (on-premise available)
IntegrationsLangChain, Vercel AI SDK, LiteLLM, 100+ frameworksGitHub, GitLab, Jenkins, VS Code, JetBrains
News HighlightMulti-modal datasets; Monitors & AlertsAcquired by OpenAI; ModelAudit launched

Choose Promptfoo if your priority is AI security — automated red teaming, guardrails, and CI/CD scanning against 50+ attack types, backed by recent OpenClaw injection analysis and ModelAudit launch. Choose Langfuse if you need production LLM observability, prompt management, and evaluations with deep framework integration (100+), now with multi-modal datasets and monitors/alerts. Both are open-source, but Promptfoo leans security-first while Langfuse is engineering-first.

Langfuse
Langfuse

Open-source LLM observability that traces, evaluates, and manages prompts from prototype to production.

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Promptfoo
Promptfoo

Automated red teaming and LLM security testing for AI applications

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Pricing
Freemium
Freemium
Plans
$0/mo
$29/mo
$199/mo
$2499/mo
$0/mo
Custom
Custom
Popularity
6.4k views
3.4k views
Skill Level
Intermediate
Intermediate
API Available
Platforms
WebAPI
CLIAPI
Categories
📡 LLM Observability & Evals
🛡️ AI Governance & Guardrails📡 LLM Observability & Evals
Features
Hierarchical traces with filtering by user, session, cost, latency, or metadata
Real-time ingestion (v4, up to 165x faster)
LLM-as-a-judge evaluations
Heuristic and boolean evaluations
Prompt versioning with one-click deploy and rollback
LLM Playground to test prompts on production inputs
Experiments with side-by-side test case comparison
Human annotation queues and golden dataset creation
Cost and latency dashboards with alerts
Pulse chart strip to spot trace outliers
Graph view with aggregated and expanded modes
Multi-modal data support (images, audio, video)
OpenTelemetry-native instrumentation
Python and TypeScript native SDKs
Automated red teaming for agents & RAGs
Context-aware attack generation (injections, jailbreaks, PII leaks)
Real-time guardrails against adversarial attacks
CI/CD integration (GitHub, GitLab, Jenkins)
Code scanning in IDE (VS Code, JetBrains)
Model security testing and monitoring
MCP proxy for secure model communication
Evaluations for prompts, models, RAG pipelines
Remediation guidance in pull requests
SaaS and self-hosted deployment (on-premise)
Real-time threat intel from 300k+ community
Supports 50+ vulnerability types
Community edition with 10k probes/month
ModelAudit: open-source scanner for ML model files (CVEs, unsafe loading)
Customizable attack profiles and target settings (Enterprise)
Integrations
LangChain
Vercel AI SDK
LiteLLM
Pydantic AI
Google ADK
CrewAI
LiveKit
OpenAI
Anthropic
Amazon Bedrock
Azure OpenAI
Mistral AI
Google Gemini
xAI
vLLM
GitHub
GitLab
Jenkins
MCP
Slack
Jira
VS Code
JetBrains

Who should pick which

  • Enterprise security engineer
    Pick: Promptfoo

    Automated red teaming for 50+ attack types, CI/CD integration, and guardrails — recently demonstrated OpenClaw injection analysis.

  • ML platform engineer
    Pick: Langfuse

    Hierarchical traces, cost/latency dashboards, and integration with 100+ frameworks like LangChain and Vercel AI SDK.

  • Solo developer building an agent
    Pick: Langfuse

    Free self-hosted option with prompt management, playground, and eval — quick to start with lightweight SDKs.

  • Compliance team (FINRA/HIPAA)
    Pick: Promptfoo

    Security testing aligned with financial/healthcare regulations, with on-premise deployment and remediation PRs.

  • Team scaling AI to billions of calls
    Pick: Langfuse

    ClickHouse-backed scalability, self-hosting under MIT, and new monitors/alerts for cost and quality.

Frequently Asked Questions

Langfuse vs Promptfoo: which should you choose?

Choose Promptfoo if your priority is AI security — automated red teaming, guardrails, and CI/CD scanning against 50+ attack types, backed by recent OpenClaw injection analysis and ModelAudit launch. Choose Langfuse if you need production LLM observability, prompt management, and evaluations with deep framework integration (100+), now with multi-modal datasets and monitors/alerts. Both are open-source, but Promptfoo leans security-first while Langfuse is engineering-first.

Can I self-host both tools?

Yes, both offer self-hosting. Promptfoo provides on-premise deployment (Enterprise). Langfuse is self-hostable under MIT license via Docker/Kubernetes.

Which tool is better for AI security?

Promptfoo is purpose-built for AI security with automated red teaming, guardrails, and CI/CD scanning. Langfuse focuses on observability, not security testing.

Do both support LLM evaluations?

Yes. Promptfoo uses automated red teaming probes and assertions. Langfuse uses LLM-as-a-judge, heuristic functions, and human annotation.

Which integrates with LangChain?

Langfuse has deep LangChain integration. Promptfoo supports OpenAI, Anthropic, and MCP but doesn't list LangChain.

What is the latest major update for Promptfoo?

Promptfoo was acquired by OpenAI, launched ModelAudit for ML file scanning, and added indirect prompt injection testing for web agents.

What is the latest major update for Langfuse?

Langfuse released multi-modal datasets, monitors & alerts, an AI assistant (public beta), and a filter search bar.

Which is more cost-effective for a startup?

Both have free tiers. Langfuse's free cloud tier and MIT-licensed self-hosting can be more cost-effective for startups without enterprise security needs.

Do they offer CI/CD integration?

Promptfoo integrates with GitHub, GitLab, and Jenkins. Langfuse integrates via GitHub Actions (alerts) but is less CI/CD-focused.

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Last reviewed: May 12, 2026