Complete pricing guide for Laminar (LMNR). Compare all plans, analyze costs, and find the perfect tier for your needs.
Not sure if free is enough? See our Free vs Paid comparison →
Still deciding? Read our full verdict on whether Laminar (LMNR) is worth it →
month
1 GB data, 100 signal runs, no overage allowed
month
3 GB data, 1,000 signal runs, overage billed at $2/GB and $0.02/run
month
10 GB data, 10,000 signal runs, overage billed at $1.50/GB and $0.015/run
custom
Custom
forever
Limited by your own infrastructure
Pricing sourced from Laminar (LMNR) · Last verified March 2026
Both are open-source LLM observability tools with self-hosting options. Laminar's differentiators are the Agent Debugger (step-restart for failed runs), browser session recording, and Signals (natural language pattern detection). Langfuse has a larger community and more third-party integrations. Pick Laminar if you're building complex, long-running agents. Pick Langfuse if you want broader ecosystem support.
Laminar auto-instruments LangChain, LlamaIndex, CrewAI, OpenAI, Anthropic Claude Agent SDK, AI SDK, LiteLLM, Browser Use, Stagehand, and OpenHands. For anything else, add custom spans using the Python or TypeScript SDK.
The SDK sends traces asynchronously without blocking agent execution. Typical overhead is under 5ms per span, which is negligible for most agent workloads.
Yes. The self-hosted version includes all core features: tracing, evaluation, datasets, and dashboards. Many teams run it in production via Docker. The managed cloud adds team collaboration, higher retention, and support SLAs.
It depends on trace verbosity and call frequency. A moderately active agent making 100 LLM calls/day generates roughly 50-100 MB/month. The free cloud tier's 1 GB handles that comfortably. High-volume production deployments with thousands of daily runs will need Hobby or Pro plans.
AI builders and operators use Laminar (LMNR) to streamline their workflow.
Try Laminar (LMNR) Now →Leading open-source LLM observability platform for production AI applications. Comprehensive tracing, prompt management, evaluation frameworks, and cost optimization with enterprise security (SOC2, ISO27001, HIPAA). Self-hostable with full feature parity.
Compare Pricing →LangSmith lets you trace, analyze, and evaluate LLM applications and agents with deep observability into every model call, chain step, and tool invocation.
Compare Pricing →Open-source LLM observability platform and API gateway that provides cost analytics, request logging, caching, and rate limiting through a simple proxy-based integration requiring only a base URL change.
Compare Pricing →Open-source LLM observability and evaluation platform built on OpenTelemetry. Self-host for free with comprehensive tracing, experimentation, and quality assessment for AI applications.
Compare Pricing →