Best AI LLM Observability Tools in 2026

For software built around large language models, observability can help you inspect requests, failures, output quality, performance, and token use. Compared on LLM trace capture, failure tracking, latency metrics, output evaluations, and token cost tracking, these tools also specify free-plan availability, retention, and paid starting prices. W&B Weave, Opik, and OpenLIT are among the options to consider. Think about which signals you need to follow in your own workflow, whether you need to evaluate outputs or diagnose failures, and how much visibility into latency and token costs is useful.