Best LLM Observability & Evaluation Tools (LLMOps) in 2026
Once an LLM app is live, you need to see what it's doing: trace calls, track cost and latency, catch regressions, and evaluate quality. These LLMOps tools give you that visibility.
Shipping an LLM feature is the easy part; keeping it reliable is where observability tools earn their place. They log every prompt and response, measure cost and latency, and let you evaluate output quality over time.
Langfuse is the popular open-source choice for tracing and evals, with a generous cloud tier and self-hosting. Helicone makes logging and a proxy gateway trivial to add — though note its post-acquisition maintenance status before committing. Braintrust focuses on evaluation and the prompt-iteration loop for teams shipping fast. Portkey is an AI gateway with observability, routing, and governance (now fully open-source). Weights & Biases (Weave) brings mature, battle-tested experiment tracking and LLM observability under one roof. Vellum leans toward product teams building and testing prompt-based workflows.
Start with tracing and cost monitoring (Langfuse or Helicone), then add structured evaluation (Braintrust or Weave) as your app matures. A gateway like Portkey is worth it once you're juggling multiple providers and need central governance.
Open-source LLM observability and evaluation
Open-source LLM observability and AI gateway in one line of code.
