Langfuse vs Arize Phoenix: 2026 comparison

Langfuse and Arize Phoenix in brief

Langfuse and Arize Phoenix help you inspect agent behavior and evaluate responses. Both offer web access, an API and open code. Langfuse also emphasizes tracking costs and model usage and managing instruction versions. Phoenix lists local data hosting and Parquet or DataFrame exports. The practical comparison therefore concerns how you observe execution, organize tests and use the results. Published pricing, hosting arrangements and output formats provide firmer distinctions than assuming that either tool performs better evaluations based on its score or category rank.

Langfuse : Langfuse tracks agent calls and steps, measures model costs and usage, and evaluates responses. It serves people who want to manage instruction versions and compare trials on datasets.

Arize Phoenix : Arize Phoenix lets teams developing agents examine execution steps and evaluate response quality. It also supports comparing prompt versions and building datasets to use when testing their systems.

Both meet the same need, which makes the comparison useful. We compare them on 10 verifiable criteria, using the same data as their profiles, collected from official sites.

Comparison table

Criterion by criterion

For each criterion: why it matters, each one's value and who has the edge. A criterion without data on both sides is not decided.

Free tier

A free tier lets you test the tool on your own examples before paying anything. Langfuse : yes. Arize Phoenix : yes. A tie on this point.

Entry price

The first paid plan, per month, gives the minimum cost of regular use; higher plans cost more. Langfuse : $29 per month. Arize Phoenix : not published. Cannot be decided: data missing on one side.

Public API

An API lets you connect the tool to your software, an automation tool or an AI agent. Langfuse : yes. Arize Phoenix : yes. A tie on this point.

Data export

Being able to get your content back avoids lock-in the day you want to switch tools. Langfuse : yes. Arize Phoenix : yes. A tie on this point.

Data hosting

Where data is stored matters for GDPR and client data: the EU or local processing make compliance simpler. Langfuse : several regions. Arize Phoenix : on device. Edge: Arize Phoenix.

Interface languages

More interface languages make the tool easier to roll out across an international team. Langfuse : not published. Arize Phoenix : 1. Cannot be decided: data missing on one side.

Platforms

The more platforms (web, desktop, mobile, extension), the better the tool fits your daily routine. Langfuse : web browser and API. Arize Phoenix : web browser and API. A tie on this point.

Open source

Public code lets you audit the tool, self-host it and keep using it if the publisher changes course. Langfuse : yes. Arize Phoenix : yes. A tie on this point.

Track record

A tool launched several years ago has a longer history: less risk of sudden shutdown, more user feedback. Langfuse : launched in 2023. Arize Phoenix : launched in 2023. A tie on this point.

Recognition

The number of reference community lists citing the tool shows how well known it is among practitioners. Langfuse : cited in 3 lists. Arize Phoenix : cited in 2 lists. Edge: Langfuse.

In charts

Our analysis

Both tools belong to the LLMOps and observability category and launched in 2023. Langfuse, published by ClickHouse, Inc., describes functions for tracking calls and agent steps, measuring costs and model usage, evaluating responses and managing instruction versions. It also supports comparing experiments on datasets. Arize Phoenix, from Arize AI, Inc., lists inspection of execution steps, response evaluation, comparison of prompt versions and creation of test datasets. These descriptions give you concrete starting points for matching requirements. They do not establish comparative evaluation accuracy or prove that a capability missing from one description is unavailable in the actual tool.

Both records list an open source pricing model and a free offering. Langfuse publishes an entry price of USD 29 per month for Core on Langfuse Cloud, with free self-hosting possible. Phoenix does not publish an entry price in the supplied information. Its free offering therefore cannot establish the rest of an unspecified pricing structure. Langfuse scores 95 out of 100 for access and transparency, compared with Phoenix’s 81; neither score measures quality. Their category ranks are first and fourth out of eighteen, with three and two community list appearances, respectively. Those indicators do not settle suitability for your workflow.

Both tools have open code, while their documented data hosting differs: mixed for Langfuse and local for Phoenix. That distinction matters when the location of data processing is a selection criterion. It does not provide a complete privacy policy or describe all data access arrangements. Langfuse lists CSV and JSON exports, programmatic export through its API and export to object storage. Phoenix lists Parquet and DataFrame. You can compare these documented outputs with your existing processes, but should not assume that unlisted formats are available or that the stated exports necessarily include every type of information held by either tool.

In daily use, Langfuse brings together documented cost tracking, usage measurement, evaluation and instruction management, addressing several supervision needs. Phoenix describes execution inspection, evaluation and test dataset preparation. Both provide web and API access, while their export formats may lead to different fits with your working processes. Phoenix lists one interface language and explicitly excludes French; Langfuse does not disclose interface languages. The records do not compare integration effort, performance or the precise limits of either free offering. Those missing details remain relevant to the decision and cannot be resolved by the access and transparency scores alone.

Depending on your situation

The right choice depends on use. For a few common situations, here are the criteria that matter and who wins (Langfuse value / Arize Phoenix value).

Personal use on a tight budget

Neither stands out on the criteria for this situation (free tier (yes / yes), entry price ($29 per month / not published), and interface languages (not published / 1)): decide with a trial.

Business use with client data

Here, Arize Phoenix has the edge: it wins 1 of the 3 criteria that matter in this situation, namely data hosting (several regions / on device), data export (yes / yes), and track record (launched in 2023 / launched in 2023).

Integration with your software

Neither stands out on the criteria for this situation (public api (yes / yes), open source (yes / yes), and platforms (web browser and API / web browser and API)): decide with a trial.

Which one to choose?

Choose Langfuse if…

• you value recognition (cited in 3 lists)

Langfuse makes sense if you need explicitly documented cost and model usage tracking alongside instruction version management and dataset experiments. Its CSV, JSON, API and object storage exports provide several published output options. The stated Cloud entry price and the possibility of free self-hosting also give you concrete access information, while leaving the exact limits of the free offering unspecified.

Choose Arize Phoenix if…

• you value data hosting (on device)

Arize Phoenix fits a requirement for local hosting, inspection of agent execution and preparation of test datasets. Its Parquet and DataFrame outputs may align with your existing analysis processes. You should account for the stated absence of French in the interface and the unpublished entry price. A free offering is documented, but the record does not describe its full scope.

Strengths and limits of each

Langfuse

• + Free tier to try it
• + Cheaper than its category median
• + Public API

Arize Phoenix

• + Free tier to try it
• + Public API
• + Public source code

The best test is still yours: take three real tasks from your day and give them to both for a week.

What about the others?

If neither suits you, look at LangSmith, Opik, Overmind, MLflow, Respan, and Prisma AIRS AI Gateway — Portkey.

Related comparisons:

• Langfuse vs LangSmith
• LangSmith vs Arize Phoenix

Conclusion

Let your monitoring requirements, hosting preference and output formats guide the decision. Langfuse documents cost tracking, a Cloud entry price and several export routes. Phoenix lists local hosting and Parquet or DataFrame outputs. Their access and transparency scores do not compare evaluation quality. Choose the published feature set that fits your work, while recognizing that the exact boundaries of free access and Phoenix’s broader pricing remain unspecified in the supplied information.