The best LLM observability tools in 2026 are Langfuse for open-source, self-hosted tracing with prompt management and evals; LangSmith for teams built on LangChain and LangGraph; Arize Phoenix for free, OpenTelemetry-native tracing you can run in one container; and Braintrust or W&B Weave if you want a hosted platform centered on experiments. Opik, Laminar and OpenLLMetry are strong open-source alternatives. Helicone still works but has been in maintenance mode since its March 2026 acquisition, so it is a weaker pick for new projects.
Ownership in this market changed fast in 2026, so this guide covers licenses, self-hosting footprint and who now owns each product, alongside features.
What LLM observability tools actually do
Traditional application monitoring tells you a request took two seconds and returned a 200. LLM observability tells you what the model was asked, which documents were retrieved, which tools were called, what each step cost in tokens, and whether the answer was any good. The core features are:
- Tracing: a nested record of every model call, retrieval and tool call in a request, with inputs, outputs, latency and token cost.
- Sessions and users: grouping traces into conversations, so you can replay what a user experienced.
- Evaluation: attaching scores to traces, from user feedback, code checks or LLM judges, and running experiments on datasets.
- Prompt management: versioning prompts outside your code and linking each trace to the prompt version that produced it.
- Dashboards and alerts: cost, latency, error and quality trends over time.
Most tools now accept OpenTelemetry data, the open standard for traces. The generative AI semantic conventions, which define attribute names for model calls, moved in 2026 to their own repository at open-telemetry/semantic-conventions-genai. Instrumenting with OpenTelemetry keeps you portable if you switch vendors later.
LLM observability tools compared
| Tool | License | Self-host | Owner (Oct 2026) | Best for |
|---|---|---|---|---|
| Langfuse | MIT core, separate enterprise directories | Yes, free | ClickHouse | Open-source default with prompts and evals |
| LangSmith | Proprietary | Enterprise plan only | LangChain | LangChain and LangGraph teams |
| Arize Phoenix | Elastic License 2.0 | Yes, free, single container | Arize, now part of Dynatrace | Simple self-hosting, OpenTelemetry-native |
| Opik | Apache 2.0 | Yes | Comet | Open-source tracing plus evals and optimization |
| W&B Weave | Apache 2.0 SDK; hosted platform | Dedicated Cloud or self-managed, via sales | Weights & Biases, part of CoreWeave | Teams already on Weights & Biases |
| Laminar | Apache 2.0 | Yes | Independent | Long-running agent traces, OpenTelemetry-native |
| OpenLLMetry | Apache 2.0 | Instrumentation only | Traceloop, part of ServiceNow | Vendor-neutral instrumentation |
| Braintrust | Proprietary; MIT autoevals library | Enterprise hybrid or on-prem | Independent | Eval-centered hosted platform |
| HoneyHive | Proprietary | Contact vendor | Independent | Hosted agent tracing and online evals |
| Helicone | Apache 2.0 | Yes | Mintlify, maintenance mode | Existing users of its gateway |
Read as a list: Langfuse, Phoenix, Opik and Laminar can all be self-hosted for free; LangSmith, Braintrust and HoneyHive are hosted-first products; OpenLLMetry is an instrumentation library that sends data to any backend rather than a full platform; and Helicone is maintained but not getting new features.
The tools in detail
Langfuse
Langfuse is the most widely recommended open-source option. It covers tracing, sessions, prompt management, datasets, experiments, human annotation queues and LLM-as-a-judge evaluators, and it is built on OpenTelemetry. ClickHouse acquired it in January 2026; the team says there are no planned licensing changes and self-hosting stays first-class (announcement).
The trade-off is operational: a production self-host runs PostgreSQL, ClickHouse, Redis or Valkey, and S3-compatible blob storage. Langfuse Cloud has a free Hobby tier with 50,000 billable units a month, and paid plans start at 29 dollars a month (pricing).
LangSmith
LangSmith, from the LangChain team, gives the tightest integration with LangChain and LangGraph, where tracing can be switched on with environment variables. It includes evals, prompt tooling and deployment features. The Developer plan is free for one seat with 5,000 base traces a month; Plus is 39 dollars per seat per month with 10,000 base traces, and self-hosting or hybrid deployment requires the Enterprise plan (pricing). We compare it head-to-head in Langfuse vs LangSmith.
Arize Phoenix
Arize Phoenix is free to self-host with no usage limits or feature gates and runs as a single Docker container. It uses OpenTelemetry and Arize's OpenInference conventions and includes evals, datasets, experiments and prompt tooling. Its license is the Elastic License 2.0, which is source-available rather than an OSI-approved open-source license; that matters mainly if you plan to offer Phoenix as a hosted service. Dynatrace completed its acquisition of Arize on October 1, 2026, and says it will keep supporting Phoenix (press release). See our Langfuse vs Arize Phoenix comparison for a detailed look at self-hosting both.
Opik
Opik, from Comet, is Apache 2.0 licensed and self-hostable. It records LLM calls, tool calls and agent steps, scores them with built-in and custom metrics, and adds prompt optimization features. Comet remains independent, which some buyers now weigh after a year of acquisitions.
W&B Weave
W&B Weave is the LLM tracing and evaluation product of Weights & Biases, which is now part of CoreWeave. It is a natural fit if your team already tracks training runs in W&B and wants traces and evals in the same place.
Laminar and OpenLLMetry
Laminar is an Apache 2.0, OpenTelemetry-native platform aimed at agents that run for hundreds of steps, with features such as session replay for browser agents and full-text search across traces. OpenLLMetry is not a dashboard but a set of OpenTelemetry instrumentations for model providers and frameworks; it can send traces to Langfuse, Phoenix, Datadog or any OTLP backend. Traceloop, its maker, joined ServiceNow in March 2026 and says OpenLLMetry will remain open source (Traceloop blog).
Braintrust and HoneyHive
Braintrust is a hosted platform built around evaluation: datasets, experiments, scorers and production logging. It has a free Starter tier and a Pro plan listed at 249 dollars a month (pricing). HoneyHive offers hosted tracing, online evaluations, monitoring, alerts and annotation queues for agent applications; see its site for pricing.
Helicone
Helicone pioneered the one-line proxy approach: route model calls through its gateway and get logging, cost tracking and caching. Mintlify acquired it in March 2026, and the team says the service stays live in maintenance mode with security updates, new model support and bug fixes (Helicone blog). Existing users are fine for now; new projects should prefer an actively developed tool.
How to choose
- Decide where data may live. If traces cannot leave your infrastructure, shortlist Langfuse, Phoenix, Opik or Laminar, or budget for an enterprise self-host of a hosted product.
- Match your framework. Heavy LangChain or LangGraph users get the smoothest start with LangSmith; everyone else should favor OpenTelemetry-based tools.
- Decide how central evaluation is. If experiments and CI gates are the main job, look hard at Braintrust, Langfuse or Phoenix, and read our playbook on how to evaluate LLM apps.
- Price your real volume. Pricing units differ: Langfuse bills per unit, meaning traces, observations and scores, while LangSmith combines seats with trace counts. Estimate with your own traffic.
- Check ownership and license. After the 2026 acquisitions, confirm the license, the roadmap commitment and the migration path before you commit.
Pros and cons of open-source versus hosted
Open-source, self-hosted
- Pros: data stays in your environment, no per-seat fees, no vendor lock-in.
- Cons: you run and upgrade the databases, and someone has to own it when things break.
Hosted
- Pros: fast setup, managed scaling, enterprise support and compliance reports.
- Cons: per-seat or usage costs grow with traffic, and data residency may require an enterprise contract.
Who each tool is for
Langfuse suits most teams that want one open-source platform for traces, prompts and evals. LangSmith suits LangChain-centric teams that prefer a managed product. Phoenix suits teams who want the lightest free self-host. Opik and Laminar suit teams who want open source from an independent vendor. Braintrust suits eval-driven teams happy with a hosted product. If you mainly need retrieval quality metrics, pair any of these with the libraries in our RAG evaluation metrics guide, and use the LLM-as-a-judge guide to set up trustworthy automated scores.
FAQ
What is LLM observability?
LLM observability is the practice of recording and analyzing what happens inside an LLM application: prompts, retrieved context, tool calls, model responses, latency, token cost and quality scores. It lets you debug individual requests and track quality and cost over time.
What are the best open-source LLM observability tools?
Langfuse, which has an MIT-licensed core, Opik and Laminar, both Apache 2.0, are fully open source and self-hostable. Arize Phoenix is free to self-host but uses the source-available Elastic License 2.0. OpenLLMetry provides open-source OpenTelemetry instrumentation that feeds any backend.
Is Langfuse free?
Yes, if you self-host it: the open-source core is free with no usage limits. Langfuse Cloud also has a free Hobby plan with 50,000 units a month and two users; paid cloud plans start at 29 dollars a month.
Does Datadog have LLM observability?
Yes. Datadog offers an LLM Observability product, which suits teams that want LLM traces next to existing infrastructure and APM data. Specialist tools usually offer deeper evaluation and prompt workflows.
Do I need OpenTelemetry for LLM tracing?
Not strictly, since most tools have their own SDKs, but instrumenting with OpenTelemetry keeps your traces portable between vendors. Langfuse, Phoenix, Laminar and OpenLLMetry are all built around it.