Weights Biases vs Langfuse

Weights & Biases and Langfuse both provide AI observability, but they come from different backgrounds — W&B from ML experiment tracking and Langfuse from LLM application monitoring.

Overview

Weights & Biases is the industry-standard ML experiment tracking platform with Weave for LLM observability, model registry, and dataset versioning. Langfuse is an open-source LLM engineering platform purpose-built for tracing, evaluating, and monitoring LLM applications in production.

Key Differences

Heritage: W&B evolved from ML experiment tracking; Langfuse was built specifically for LLM applications from day one. LLM focus: Langfuse's every feature is designed for LLM workflows. W&B's Weave is a newer product within a broader platform. Self-hosting: Langfuse is MIT-licensed and easily self-hosted. W&B self-hosting requires enterprise licensing. Cost: Langfuse offers a generous free tier (50K observations). W&B is free for individuals but $50/user/month for teams. Scope: W&B covers the full ML lifecycle (training, evaluation, deployment). Langfuse focuses on production LLM observability.

Verdict

Choose Weights & Biases if you're training custom models and need the full ML lifecycle platform with experiment tracking. Choose Langfuse if you're building LLM applications and need purpose-built, open-source observability with self-hosting options.