List of the Best LLM Observability & Evaluation Software in 2026

These tools answer two different questions and most teams need both. Tracing tells you what your application did — which prompts ran, what the retriever returned, where latency and cost went. Evaluation tells you whether the output was any good. LangSmith, Langfuse, Helicone and Traceloop lead on the first; Confident AI, Patronus, TruLens and Arize Phoenix lead on the second.

Self-hosting is the fastest way to shorten the list. Prompts and completions routinely contain customer data, and many teams cannot send them to a hosted service. Langfuse, Phoenix, Opik, Lunary, Athina and LangWatch all run in your own environment.

If you already run an observability stack, Traceloop's OpenLLMetry sends traces into Datadog, Grafana or Honeycomb rather than asking you to adopt another dashboard.

Portkey is the odd one out and worth knowing about: it sits in the request path as a gateway, so it adds routing, fallback and caching alongside observability, and captures traces without any application instrumentation.

For agents specifically, single-response evaluation misses the failure mode that matters — an agent can answer every individual turn well and still fail the conversation. Maxim and LangWatch test at the scenario level.