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Langfuse VS TokenCalculator.dev

Compare Langfuse VS TokenCalculator.dev and see what are their differences

Langfuse

Langfuse is an open-source LLM engineering platform that helps teams collaboratively debug, analyze, and iterate on their LLM applications.

Rating
0 reviews
Pricing
Open source
Alternatives Is it good?
TokenCalculator.dev

Count LLM tokens and estimate API cost from text, PDF, DOCX, code, data files, and images with privacy-first browser-based processing.

Rating
0 reviews
Pricing
Open source Free Free trial
Alternatives Is it good?
Thalam
OpenAI-compatible API gateway for GPT, Claude, Gemini, DeepSeek, Qwen, Kling and more. One key, one endpoint, one bill. Pay per token, no lock-in. sponsored

Which is more popular?

Based on our record, Langfuse seems to be more popular. It has been mentioned 33 times since March 2021.

social mentions
33 vs 0
AI popularity
98% vs 2%
alternatives listed
240+ vs 3

Base details

Website, pricing, platforms and company facts side by side.

Langfuse
TokenCalculator.dev
Website langfuse.com tokencalculator.dev
Pricing
Open source
Open source Free Free trial Official pricing
Platforms —
N8n REST API NPM Activepieces +1
Company Startup from the United States Startup from India · 1 - 9 employees · 2026
Listed in
Help Desk Productivity User Engagement AI +1
LLM Observability AI AI Tools LLM +1

About Langfuse and TokenCalculator.dev

In their own words, as submitted to SaaSHub.

Langfuse
TokenCalculator.dev

Langfuse is an open-source LLM engineering platform designed to empower developers by providing insights into user interactions with their LLM applications. We offer tools that help developers understand usage patterns, diagnose issues, and improve application performance based on real user data....

Read more about Langfuse

TokenCalculator.dev is a privacy-first, 100% browser-based LLM token counter and API cost estimator designed for AI engineers, developers, and product teams. Unlike conventional text-only calculators that require uploading sensitive prompts to third-party servers, TokenCalculator.dev processes...

Read more about TokenCalculator.dev

Features and specs

What each product offers, as listed by its team.

Langfuse 3 features
TokenCalculator.dev 5 features
  • User-Friendly Interface
    Langfuse offers a clean and intuitive interface that makes it easy for users to navigate and use the platform efficiently, regardless of their technical skill level.
  • Integration Capabilities
    The platform provides a variety of APIs and integration options, allowing users to seamlessly connect Langfuse with other applications and services they use.
  • Comprehensive Analysis Tools
    Langfuse offers advanced analysis tools that help users to gain insights from their language data, improving decision-making and strategy development.

Possible disadvantages

  • Limited Language Support
    While Langfuse offers a range of language options, it may not support as many languages as some global companies require, potentially limiting its usability for diverse linguistic needs.
  • Pricing Model
    The pricing model of Langfuse might be considered expensive for small businesses or startups with a limited budget, which can make it less accessible to those users.
  • Learning Curve for Advanced Features
    While the basic features are easy to use, some advanced functionalities might have a steep learning curve, requiring more time and effort from users to fully leverage them.
  • 100% Client-Side Privacy
    Calculates tokens and costs entirely in the browser with zero server uploads or prompt logging.
  • Multi-Modal Vision Token Estimation
    Measures image tokens for PNG, JPEG, WebP, and GIF using official tile, patch, and media rules.
  • Document & Code Ingestion
    Extracts text and counts tokens from local PDF, DOCX, and codebase files across 20+ languages up to 12 MB.
  • Multi-Model Cost Comparison
    Live context-window fit and API cost estimation across OpenAI, Claude, Gemini, and DeepSeek.
  • Exact BPE Tokenization
    Uses local o200k_base BPE tokenization alongside deterministic provider-calibrated projections.

Videos

Walkthroughs and reviews on video.

Langfuse 1 video + Add
TokenCalculator.dev 0 videos + Add

Langfuse in two minutes

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Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Langfuse
TokenCalculator.dev
98% 98%
AI
2% 2%
0% 0%
LLM Observability
100% 100%
100% 100%
Developer Tools
0% 0%
100% 100%
Productivity
0% 0%

Questions & Answers

As answered by people managing Langfuse and TokenCalculator.dev.

What makes your product unique?

TokenCalculator.dev's answer:

TokenCalculator.dev is a 100% browser-based, privacy-first token counter and API cost estimator that handles multimodal payloads without sending data to a server. Unlike conventional text-only counters, it processes pasted text, local documents (PDF, DOCX, and code in 20+ languages up to 12 MB), and image files (PNG, JPEG, WebP, GIF) entirely on the client side across OpenAI, Claude, Gemini, and DeepSeek.

Why should a person choose your product over its competitors?

TokenCalculator.dev's answer:

Most token counters either require pasting text into third-party cloud servers or only support basic text inputs for a single provider. TokenCalculator.dev guarantees zero prompt or document retention, supports direct document parsing (PDF/Word/code) and visual tile/patch token calculations, and lets you compare live input costs and context-window fits across four major frontier providers simultaneously.

How would you describe the primary audience of your product?

TokenCalculator.dev's answer:

AI engineers, software developers, technical product managers, and researchers who build LLM-powered applications, design RAG pipelines, or manage API token budgets and context window limits.

What's the story behind your product?

TokenCalculator.dev's answer:

Developers frequently face unexpected API costs, context overflow errors, and privacy concerns when testing prompts and document payloads with online token tools. TokenCalculator.dev was created to provide a fast, transparent, and completely offline-capable developer utility that reliably measures realistic production payloads—including codebases, documents, and images—without compromising sensitive data.

Which are the primary technologies used for building your product?

TokenCalculator.dev's answer:

Built with modern web technologies using TypeScript and WebAssembly/JavaScript for client-side BPE tokenization (o200k_base), browser-native text extraction parsers for PDF and DOCX, client-side Canvas APIs for image dimension inspection, and integrated model pricing metadata.

Who are some of the biggest customers of your product?

TokenCalculator.dev's answer:

Independent AI Engineers & Full-Stack Developers RAG & Agentic Workflow Builders Open-Source Software Contributors Tech Startups budgeting multi-model API deployments

User comments

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Reviews and articles

External articles and on-site reviews we used to compare the two products.

Langfuse no reviews yet
TokenCalculator.dev no reviews yet

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Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Langfuse 33 mentions
TokenCalculator.dev 0 mentions
  • Set up a .NET application w/th OpenTelemetry, and trace/evaluate in Langfuse
    We have researched and experimented with several AI evaluation platforms, including Arize Phoenix, Microsoft Foundry, and Langfuse. After evaluating them against our requirements and roadmap, we shortlisted Microsoft Foundry and Langfuse... - Source: dev.to / 3 days ago
  • How to change an LLM prompt in production without a code deploy
    Langfuse is the other serious option in this category if you also want observability, evals and traces bundled with prompt management. Different scope, more setup, worth comparing honestly. - Source: dev.to / 25 days ago
  • Should Your Prompt Store Pick Your Model
    Langfuse with Microsoft.Extensions.AI has an appealing story: update prompts without redeploying. A prompt fetches its config blob—model, tokens, temperature—which the code passes straight to the LLM. - Source: dev.to / 28 days ago

View more

Tracking TokenCalculator.dev since Sep 2026.

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