DeepYard

Helicone vs Langfuse

Side-by-side comparison built from DeepYard's structured catalog. Content updated Aug 21, 2026.

Direct Answer

Helicone suits teams needing freemium $20/mo, azure openai focus, and 6,093 GitHub stars in current listing data. Langfuse suits teams needing freemium free tier, evaluation focus, and 33,539 GitHub stars in current listing data. This summary reflects catalog metadata only for decision support, not independent testing.

What this comparison weighs

  • Pricing and free-tier availability
  • License model and deployment fit
  • GitHub adoption and contributor depth
  • Catalog tags, integrations, and supported workflows
H

Helicone

Open-source LLM observability proxy with one-line integration

OSSfreemium
6.1K6d ago96
Visit GitHub
L

Langfuse

Open-source LLM engineering platform — traces, evals, prompt management — 23K+ stars

OSSfreemium
33.5Ktoday196
Visit GitHub
MetricHeliconeLangfuse
GitHub Stars6.1K33.5K
Contributors96196
Last CommitAug 16, 2026Aug 22, 2026
Open Issues150811
Licenseopen-sourceopen-source
Pricingfreemiumfreemium
Free TierYesYes
Categorydev-toolsdev-tools
TrendingNoNo

Choose Helicone if you need

  • • Helicone is the stronger pick when Azure Openai matters because that capability is listed only on its profile.
  • • Helicone is the cleaner fit if you specifically need Proxy workflows from the catalog tags.

Choose Langfuse if you need

  • • Langfuse stands out for Evaluation workflows that are not listed for Helicone.
  • • Langfuse is the stronger pick when Llamaindex matters because that capability is listed only on its profile.
  • • Langfuse shows broader GitHub adoption with 33,539 stars versus 6,093 for Helicone.

Meaningful differences

  • • Pricing model: Helicone is listed as freemium from $20/mo, while Langfuse is listed as freemium.
  • • Workflow emphasis: Helicone highlights Observability, while Langfuse highlights Evaluation.
  • • GitHub adoption: Helicone shows 6,093 stars versus 33,539 for Langfuse.
  • • Contributor count: Helicone lists 96 contributors and Langfuse lists 196.

Shared capabilities

  • • Observability
  • • Open Source
  • • Openai
  • • Anthropic
  • • Langchain

Shared Tags

observabilityopen-source

Only in Helicone

proxycost-trackingllm-ops

Only in Langfuse

tracingevaluationprompt-managementanalytics

Limitations and evidence

  • • DeepYard compares structured public metadata; this is not an independent benchmark unless a test record is shown.
  • • Signals such as stars, contributors, and last commit indicate public activity, not purchase fit or runtime quality.
  • • Pricing and feature coverage reflect the stored listing snapshot and may lag vendor changes between refreshes.

Source links

Manifest content date: 2026-08-21

About Helicone

Helicone is an open-source observability platform for LLMs that works as a transparent proxy — add one line to your base URL and immediately get request logging, cost tracking, latency histograms, and user-level analytics. It supports caching, rate limiting, and prompt management out of the box, making it one of the fastest ways to add production visibility to any OpenAI-compatible API call.

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About Langfuse

Langfuse is an open-source LLM engineering platform providing observability, analytics, and prompt management. Features distributed tracing for complex agent chains, evaluation scoring, prompt versioning and A/B testing, dataset management, and cost tracking. Integrates with LangChain, LlamaIndex, OpenAI SDK, and any LLM framework via OpenTelemetry.

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