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Langfuse vs LangSmith Comparison

Last updated:

Langfuse

4.7(185 reviews)

Starting at Free free

  • Small Business
  • Mid-Market

Langfuse is an open-source LLM engineering platform for tracing, evaluation, prompt management, and metrics. It provides detailed traces of LLM application executions — capturing every LLM call, tool use, retrieval step,…

LangSmith

4.5(310 reviews)

Starting at Free free

  • Small Business
  • Mid-Market

LangSmith is the LLMOps observability and evaluation platform built by LangChain for teams developing production LLM applications. It provides tracing, debugging, and evaluation for any LLM application — not just LangCha…

Langfuse leads on user satisfaction with a 4.7-star rating across 185 reviews.

Langfuse vs LangSmith — at a glance

FeatureLangfuseLangSmith
Rating4.7 / 54.5 / 5
Reviews185310
Starting priceFree freeFree free
Free trial No No
Free version No No
Best forSmall Business, Mid-Market, EnterpriseSmall Business, Mid-Market, Enterprise
CategoryMLOps PlatformsMLOps Platforms
PlatformsCloud, On-Premise, LinuxCloud, On-Premise
APIAvailableAvailable
Support modesGitHub Issues, Discord Community, Email Support, Enterprise SupportDiscord Community, Help Center, Email Support, Enterprise Support

Key differences between Langfuse and LangSmith

  • Pricing: Langfuse starts at Free free, while LangSmith starts at Free free.
  • User satisfaction: Langfuse scores higher with a 4.7-star average.
  • Deployment: Langfuse supports Cloud, On-Premise, Linux; LangSmith supports Cloud, On-Premise.

Langfuse vs LangSmith — find the better fit before you commit.

01

Which tool fits your team best

02

Which is actually cheaper for your team size

03

Where each product wins, per real buyers

Most MLOps Platforms tools look identical on paper. This comparison cuts to the differences that matter — pricing structure, team fit, and what real buyers found after signing up.

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Biggest differences

Start here before you go deeper into features.

Langfuse

Best for

Small Business, Mid-Market, Enterprise

LangSmith

Best for

Small Business, Mid-Market, Enterprise

Langfuse typically suits Small Business and Mid-Market. LangSmith tends to fit Small Business and Mid-Market better. The right choice depends on your team size, workflow, and whether a free trial matters.

Description

Langfuse is an open-source LLM engineering platform for tracing, evaluation, prompt management, and metrics. It provides detailed traces of LLM application executions — capturing every LLM ... Read More about Langfuse

LangSmith is the LLMOps observability and evaluation platform built by LangChain for teams developing production LLM applications. It provides tracing, debugging, and evaluation for any LLM ... Read More about LangSmith

Entry Level Pricing

  • Starts from Free
  • Starts from Free

Free Trial Availability

  • No free trial
  • No free trial

SpotScore

What's this? ↗

9.4/10

9.0/10

User Ratings

Based on verified Spotsaas reviews
Get pricing help
Get pricing help

Where each option fits best

See where each product is strongest, which teams it fits, and what causes buyers to keep looking — before you commit.

Based on buyer reviews and verified product data collected by Spotsaas.

Strengths

Key strengths

Langfuse

  • Data Sovereignty for AI Traces: Self-hosted MIT deployment keeps all LLM traces, prompts, and evaluation data on company infrastructure — critical for regulated industries.
  • Free at Scale: 50k free cloud traces plus unlimited self-hosted cover most production AI applications without per-trace cost anxiety.
  • Product-Level AI Analytics: Session grouping lets you analyze how users interact with AI features across multi-turn conversations — beyond per-call debugging.

LangSmith

  • Debug LLM Failures Fast: Full call traces with inputs, outputs, latency, and token counts for every LLM call — no more guessing why an AI chain failed.
  • Prevent Prompt Regressions: Automated evaluation runs on datasets catch quality regressions when prompts change, before they reach users.
  • Monitor Production AI Quality: Real-time dashboards track LLM latency, error rates, and output quality — the same visibility layer backend engineers expect for APIs.
Best fit

Best fit

Langfuse

  • European and regulated-industry teams self-hosting LLM observability to maintain data residency compliance
  • Early-stage AI startups instrumenting production LLM applications at zero cost with the cloud free tier
  • Teams running systematic LLM-as-judge evaluations to catch prompt quality regressions before deployment

LangSmith

  • AI engineering teams debugging complex multi-step LLM chains that produce unexpected outputs
  • Teams running systematic evaluation of prompt changes before deploying to production
  • ML platform teams building shared observability infrastructure for multiple AI product teams

Software Demo

Demo

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How do Langfuse and LangSmith Compare on Features?

Total Features

8 Features

9 Features

Unique Features

No unique features

No unique features

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Compare Langfuse and LangSmith on pricing

Review starting price, plan structure, and free-trial access side by side so you can see which option fits your budget and buying process.

Pricing Option

      Starting From

      • Free
      • Free

      Pricing Plans

      • Developer

        Free

        • 5k traces/month

        • All core features

        • Community support

      • Plus

        $39

        paid

        • 100k traces/month

        • Team features

        • Priority support

      • Enterprise

        Custom

        paid

        • Unlimited traces

        • SSO

        • On-premise

        Show more +

      Other Details

      Organization Types supported

          Platforms Supported

              Modes of support

              • 24/7 (Live rep)
              • Business Hours
              • Online
              • 24/7 (Live rep)
              • Business Hours
              • Online

              API Support

              • Available
              • Available
              Get help choosing
              Get help choosing

              Langfuse User Reviews & Rating Comparison

              User Ratings

              4.7

              (based on 185 reviews)

              4.5

              (based on 310 reviews)

              Rating Distribution

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              0

              0

              0

              0

              0

              0

              0

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              Spotsaas Editor’s POV generated by AI

              Buyer sentiment

              Buyer sentiment is very strong across 185 reviews, with consistently positive feedback.

              What buyers like

              • MIT open-source license with Docker-based self-hosting means teams with data privacy requirements can run full LLM observability without sending traces to a third-party cloud.
              • Generous free cloud tier (50k traces/month) covers most early-stage AI applications without any cost.
              • Session-level trace grouping links multiple LLM calls into user sessions — enabling product-level analysis of where users encounter AI failures.

              Common complaints

              • Smaller ecosystem and fewer integrations than LangSmith — some niche frameworks require manual instrumentation rather than automatic SDK integration.
              • Self-hosting requires Docker knowledge and ongoing maintenance; small teams without DevOps support may prefer the managed cloud.

              Buyer sentiment

              Buyer sentiment is very strong across 310 reviews, with consistently positive feedback.

              What buyers like

              • Framework-agnostic tracing works with any LLM provider (OpenAI, Anthropic, Mistral) and any orchestration framework, not just LangChain.
              • Prompt Hub enables version-controlled prompt management with one-click rollback — replacing ad-hoc string management in code.
              • Evaluation datasets and automated test runs enable regression testing across prompt versions, catching quality regressions before they reach production.

              Common complaints

              • Built by LangChain, so teams using competing orchestration frameworks may find occasional rough edges in non-LangChain integrations.
              • Trace storage costs scale with volume — high-frequency production applications need to budget carefully for trace retention.

              Pros and Cons

              • MIT open-source license with Docker-based self-hosting means teams with data privacy requirements can run full LLM observability without sending traces to a third-party cloud.

              • Generous free cloud tier (50k traces/month) covers most early-stage AI applications without any cost.

              • Session-level trace grouping links multiple LLM calls into user sessions — enabling product-level analysis of where users encounter AI failures.

              • Smaller ecosystem and fewer integrations than LangSmith — some niche frameworks require manual instrumentation rather than automatic SDK integration.

              • Self-hosting requires Docker knowledge and ongoing maintenance; small teams without DevOps support may prefer the managed cloud.

              • Framework-agnostic tracing works with any LLM provider (OpenAI, Anthropic, Mistral) and any orchestration framework, not just LangChain.

              • Prompt Hub enables version-controlled prompt management with one-click rollback — replacing ad-hoc string management in code.

              • Evaluation datasets and automated test runs enable regression testing across prompt versions, catching quality regressions before they reach production.

              • Built by LangChain, so teams using competing orchestration frameworks may find occasional rough edges in non-LangChain integrations.

              • Trace storage costs scale with volume — high-frequency production applications need to budget carefully for trace retention.

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              Disclaimer: This research has been collated from a variety of authoritative sources. We welcome your feedback at [email protected].

              Frequently asked questions

              Which is better, Langfuse or LangSmith?
              Langfuse edges out the other on user ratings (4.7 vs 4.5). That said, the best pick depends on your use case — use the comparison tables above to evaluate each dimension.
              Do Langfuse and LangSmith offer a free trial?
              Neither Langfuse nor LangSmith currently lists a free trial.
              What is the starting price of Langfuse vs LangSmith?
              Langfuse starts at Free free. LangSmith starts at Free free.