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Tools/Langfuse/vs LangSmith
Langfuse

Langfuse

observability
vs
LangSmith

LangSmith

observability

Langfuse vs LangSmith — Comparison

15 integrations1 features870,710 npm/wkMerger / Acquisition
15 integrations14 featuresSeries B
Overview
What each tool does and who it's for

Langfuse

Traces, evals, prompt management and metrics to debug and improve your LLM application.

Langfuse is recognized for its capability to effectively track LLM calls, providing visibility into AI operations which is crucial for production environments. However, some users have raised concerns about its lack of understanding of agent topology and potential interoperability limitations with other tracing formats. There isn't much specific sentiment mentioned about pricing, but there seems to be an implication that it's a paid solution compared to some open-source alternatives. Overall, Langfuse is appreciated as a valuable tool for observability in AI, though it faces some competition from both paid and open-source tools offering varied features.

LangSmith

View in LangSmith

LangSmith is recognized for its capabilities in providing observability for AI agents, a necessary feature due to the risk associated with running these agents in production environments. A key complaint highlighted is that LangSmith is a cloud-only service with paid access, which may not be ideal for all users, especially those preferring open-source alternatives. The general sentiment around its pricing is somewhat negative, as users express a preference for non-commercial options. Overall, LangSmith appears to have a solid reputation for its functional strengths but faces criticism regarding its availability and cost structure.

Key Metrics
24,100
GitHub Stars
—
2,434
GitHub Forks
—
870,710
npm Downloads/wk
—
19,249,322
PyPI Downloads/mo
—
Mention Velocity
How discussion volume is trending week-over-week

Langfuse

+100% vs last week

LangSmith

Stable week-over-week
Where People Discuss
Mention distribution across platforms

Langfuse

Reddit
62%
YouTube
24%
Hacker News
10%
Dev.to
5%

LangSmith

Reddit
46%
YouTube
38%
Hacker News
15%
Community Sentiment
How developers feel about each tool based on mentions and reviews

Langfuse

19% positive81% neutral0% negative

LangSmith

15% positive77% neutral8% negative
Pricing

Langfuse

subscription + tiered

Pricing found: $29 / month, $8/100k, $199 / month, $8/100k, $300/mo

LangSmith

Use Cases
When to use each tool

Langfuse (8)

Monitoring LLM performance in productionTracking API usage and costsAnalyzing user interactions with LLMsIdentifying bottlenecks in LLM workflowsDebugging multi-agent systemsOptimizing LLM response timesConducting A/B testing on LLM outputsCollecting feedback for LLM improvements

LangSmith (9)

Monitoring AI agent performance in productionDebugging issues in multi-agent systemsEvaluating the effectiveness of AI agentsPreventing data loss in AI applicationsManaging deployment of AI agentsIntegrating observability into CI/CD workflowsTracking user interactions with AI agentsAnalyzing agent behavior over timeSetting up alerts for performance anomalies
Features

Only in Langfuse (1)

Gain deep visibility into your traces

Only in LangSmith (14)

Agent debugging toolsPerformance monitoring dashboardsReal-time observability metricsError tracking and reportingAgent performance evaluationDeployment management for AI agentsCustomizable alerting systemIntegration with CI/CD pipelinesUser activity trackingData loss prevention mechanismsMulti-agent system supportCloud-based infrastructureVersion control for agent configurationsCollaboration tools for development teams
Integrations

Shared (11)

OpenAIAWS LambdaSlackZapierGitHubGoogle Cloud PlatformMicrosoft AzureJiraDatadogPrometheusGrafana

Only in Langfuse (4)

ClickhouseTrelloNotionSentry

Only in LangSmith (4)

CircleCIDockerKubernetesTwilio
Developer Ecosystem
18
GitHub Repos
—
828
GitHub Followers
—
20
npm Packages
—
22
HuggingFace Models
—
Pain Points
Top complaints from reviews and social mentions

Langfuse

cost tracking (3)anthropic bill (1)surprise bill (1)cost monitoring (1)usage monitoring (1)token usage (1)

LangSmith

cost tracking (4)anthropic bill (1)openai bill (1)token usage (1)
Top Discussion Keywords
Most mentioned keywords from community discussions

Langfuse

cost tracking (3)anthropic bill (1)surprise bill (1)cost monitoring (1)usage monitoring (1)token usage (1)

LangSmith

cost tracking (4)anthropic bill (1)openai bill (1)token usage (1)
Latest Videos
Recent uploads from official YouTube channels

Langfuse

Langfuse Context: All things MCP with Adam Jones (Tech Lead at Anthropic)

Langfuse Context: All things MCP with Adam Jones (Tech Lead at Anthropic)

Jan 6, 2026

Continuous Evaluation, Monitoring, and Operations of AI Agents with AWS Bedrock AgentCore & Langfuse

Continuous Evaluation, Monitoring, and Operations of AI Agents with AWS Bedrock AgentCore & Langfuse

Nov 25, 2025

Collect User Feedback of your LLM Agent in Langfuse

Collect User Feedback of your LLM Agent in Langfuse

Nov 14, 2025

Langfuse Launch Week Day 6: Dataset Schema Enforcement & Folders

Langfuse Launch Week Day 6: Dataset Schema Enforcement & Folders

Nov 8, 2025

LangSmith

No YouTube channel

Product Screenshots

Langfuse

Langfuse screenshot 1Langfuse screenshot 2

LangSmith

No screenshots

What People Talk About
Most discussed topics from community mentions

Langfuse

pricing3
api3
model selection3
agents3
cost optimization3
scalability2
open source2
streaming2

LangSmith

pricing1
performance1
documentation1
api1
open source1
deployment1
model selection1
RAG1
Top Community Mentions
Highest-engagement mentions from the community

Langfuse

OpenTelemetry just standardized LLM tracing. Here's what it actually looks like in code.

Every LLM tool invents its own tracing format. Langfuse has one. Helicone has one. Arize has one. If...

Dev.toby vola-treblaneutral source

LangSmith

Ask HN: How are you monitoring AI agents in production?

With the recent incidents (DataTalks database wipe by Claude Code, Replit agent deleting data during code freeze), it&#x27;s clear that running AI agents in production without observability is risky.<p>Common failure modes I&#x27;ve seen: no visibility into what the agent did step-by-step, surprise

Hacker Newsby jairoohpositive source
Company Intel
information technology & services
Industry
information technology & services
19
Employees
98
$4.1M
Funding
$260.0M
Merger / Acquisition
Stage
Series B
Supported Languages & Categories

Only in Langfuse (5)

AI/MLDevOpsSecurityAnalyticsDeveloper Tools
View Langfuse Profile View LangSmith Profile