TokenCurb vs LangFuse: LLM Cost Tracking Compared

If you're evaluating LLM observability tools, you've probably come across LangFuse — the popular open-source platform for tracing, evals, and prompt management.

But LangFuse wasn't built primarily for cost visibility. TokenCurb was. Here's an honest comparison so you can choose the right tool for your team.

The cost visibility gap

Both tools help you understand LLM usage, but they start from different problems. LangFuse solves for 'what happened in my LLM pipeline?' TokenCurb solves for 'where did my budget go and how do I spend less?'

LangFuse strengths

LangFuse is a full-stack LLM engineering platform. It excels at:

• Deep tracing for complex agent chains and multi-step workflows
• Integrated evaluation (evals) with LLM-as-a-judge scoring
• Prompt management with version control and playground
• Open-source: self-host or use their cloud
• Rich metadata filtering and search on traces

TokenCurb strengths

TokenCurb is purpose-built for cost governance. It excels at:

• Per-feature cost breakdown — not just total spend
• Agent loop detection — automatic flagging of 10×+ token usage
• Spike alerts before costs hit your invoice (Slack, email, webhook)
• Model routing suggestions — which calls can run cheaper
• Simpler setup: no pipeline instrumentation needed

When to choose LangFuse

• You need deep agent tracing and debugging capabilities
• You want an integrated eval framework for quality monitoring
• Your team is already invested in the LangChain ecosystem
• You need prompt management with version control

When to choose TokenCurb

• Your primary pain is surprise LLM bills, not trace debugging
• You need cost breakdown by feature, user, or agent for product decisions
• Agent loops are silently eating your budget
• You want proactive alerts before costs spike

Verdict

LangFuse and TokenCurb complement each other. If you need deep tracing and evals, use LangFuse. If your main problem is cost visibility and budget control — or you want both — add TokenCurb for the cost layer. Many teams use LangFuse for debugging and TokenCurb for cost management.