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Labelbox
Beschriftung · 1.1M monatliche besuche

Labelbox ist eine umfassende datenzentrierte KI-Plattform oder "Data Factory", die für KI-Teams entwickelt wurde. Sie bietet integrierte Software, Expertendienste und einen Talentmarktplatz zur Erstellung, Verwaltung und Bewertung hochwertiger Trainingsdaten für fortschrittliche KI-Modelle, einschließlich LLMs und multimodaler Systeme.

VS
SuperAnnotate
Beschriftung · 406.4K monatliche besuche

SuperAnnotate ist eine führende KI-Datenplattform, die die gesamte Datenpipeline für maschinelles Lernen optimiert. Sie ermöglicht es Teams, hochwertige multimodale Datensätze (Bild, Video, Text, Audio) zu annotieren, zu verwalten und zu kuratieren, um die Modellentwicklung zu beschleunigen, einschließlich komplexer Workflows wie RLHF, RAG und SFT. Sie wurde entwickelt, um die Modellgenauigkeit und -effizienz zu verbessern.

Labelbox vs SuperAnnotate: Preise, Funktionen und Traffic

Vergleiche Labelbox und SuperAnnotate nach Positionierung, Preis, Funktionen, Traffic und Nutzerfeedback.

Aktualisiert 05.08.2026

Produktübersicht

Labelbox Produktübersicht

Labelbox ist eine umfassende datenzentrierte KI-Plattform oder "Data Factory", die für KI-Teams entwickelt wurde. Sie bietet integrierte Software, Expertendienste und einen Talentmarktplatz zur Erstellung, Verwaltung und Bewertung hochwertiger Trainingsdaten für fortschrittliche KI-Modelle, einschließlich LLMs und multimodaler Systeme.

Preview

SuperAnnotate Produktübersicht

SuperAnnotate ist eine führende KI-Datenplattform, die die gesamte Datenpipeline für maschinelles Lernen optimiert. Sie ermöglicht es Teams, hochwertige multimodale Datensätze (Bild, Video, Text, Audio) zu annotieren, zu verwalten und zu kuratieren, um die Modellentwicklung zu beschleunigen, einschließlich komplexer Workflows wie RLHF, RAG und SFT. Sie wurde entwickelt, um die Modellgenauigkeit und -effizienz zu verbessern.

Preview

Detailed feature comparison

FeatureLabelboxSuperAnnotate
HauptkategorieBeschriftungBeschriftung
Hinzugefügt2025-08-112025-08-05
PreismodellFreemiumFreemium
Offizielle Websitelabelbox.comwww.superannotate.com
ProdukttypWebsiteWebsite
Performance data
NutzerbewertungNicht verifiziertNicht verifiziert
Kommentare00
Monatliche Besuche1.1M406.4K
Monatliches Wachstum19.3%2.2%
Favoriten8789
DetailsDetails ansehenDetails ansehen

Labelbox vs SuperAnnotate monthly traffic

Compare Labelbox and SuperAnnotate by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.

How to interpret the traffic data

In the Labelbox vs SuperAnnotate monthly traffic comparison, Labelbox currently shows 1.1M visits and SuperAnnotate shows 406.4K; Labelbox has about 2.7 times the visible traffic of SuperAnnotate, an absolute difference of about 688.7K visits. This reflects visible reach, not feature quality or paid users.

Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.

Labelbox monthly traffic:

Latest traffic

Monatliche Besuche
1.1M
Ø Besuchsdauer
4:51
Seiten pro Besuch
7.12
Absprungrate
29.75%
Data updated 2026-06-15

Monthly traffic trend

  • 2025/9: 1M Monatliche Besuche
  • 2026/1: 1.1M Monatliche Besuche
  • 2026/2: 1.1M Monatliche Besuche
  • 2026/3: 848.5K Monatliche Besuche
  • 2026/4: 918.3K Monatliche Besuche
  • 2026/5: 1.1M Monatliche Besuche

Top-Regionen

Top 5 countries/regions
Country/regionPercentageTraffic
🇺🇸United States51.51%564.1K
🇮🇳India16.98%185.9K
🇫🇷France13.54%148.3K
🇲🇽Mexico10.56%115.6K
🇪🇬Egypt7.41%81.1K

Traffic-Quellen

Source typePercentageTraffic
Direkt60.34%660.7K
Verweis29.82%326.5K
E-Mail9.84%107.8K

Suchbegriffe

alignerralignerr loginlabel boxlabelboxlabelbox login

SuperAnnotate monthly traffic:

Latest traffic

Monatliche Besuche
406.4K
Ø Besuchsdauer
4:18
Seiten pro Besuch
4.91
Absprungrate
34.06%
Data updated 2026-06-15

Monthly traffic trend

  • 2025/9: 234.7K Monatliche Besuche
  • 2026/1: 368.8K Monatliche Besuche
  • 2026/2: 400K Monatliche Besuche
  • 2026/3: 541K Monatliche Besuche
  • 2026/4: 397.6K Monatliche Besuche
  • 2026/5: 406.4K Monatliche Besuche

Top-Regionen

Top 5 countries/regions
Country/regionPercentageTraffic
🇺🇸United States64.07%260.4K
🇮🇳India20.8%84.5K
🇩🇪Germany6.28%25.5K
🇧🇩Bangladesh5.79%23.5K
🇮🇱Israel3.06%12.4K

Traffic-Quellen

Source typePercentageTraffic
Direkt83.64%339.9K
E-Mail8.59%34.9K
Verweis7.77%31.6K

Suchbegriffe

data annotationdataannotationdiffusion modelssuperannotatewhat is data annotation
Traffic-based selection guidance: If public market visibility is an important first-pass criterion, investigate Labelbox first. The final choice should still follow taxonomy, use case, and a real trial because higher traffic does not prove broader capabilities or better workflow fit.

Usage comparison

Compare the core capabilities of Labelbox and SuperAnnotate

Labelbox Core features

Beschriftung
Workflow-Management
Maschinelles Lernen

SuperAnnotate Core features

Beschriftung
Workflow-Management
MLOps

Use cases

Labelbox Use cases

Computer Vision
Datenannotation
Datenlabeling
Mensch-in-der-Schleife
Großes Sprachmodell
KI-Training
maschinelles Lernen
Modellbewertung
Multimodale KI
NLP
Reinforcement Learning

SuperAnnotate Use cases

Computer Vision
Datenannotation
Datenlabeling
Mensch-in-der-Schleife
Großes Sprachmodell
KI-Datenplattform
KI-Trainingsdaten
Dataset-Management
MLOps
Retrieval-Augmentierte Generierung
RLHF
SFT

Labelbox vs SuperAnnotate:In-depth comparison and selection guidance

First decide whether the products solve the same kind of need

This in-depth Labelbox vs SuperAnnotate comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. Labelbox is primarily listed under “Beschriftung”, while SuperAnnotate is primarily listed under “Beschriftung”, so the first decision is whether your actual task matches their recorded scope.

The structured fields currently show these decision-relevant differences: Monthly visits (Labelbox: 1.1M; SuperAnnotate: 406.4K); Monthly growth (Labelbox: 19.3%; SuperAnnotate: 2.2%); Favorites (Labelbox: 87; SuperAnnotate: 89); Website (Labelbox: labelbox.com; SuperAnnotate: www.superannotate.com); Added (Labelbox: 2025-08-11; SuperAnnotate: 2025-08-05). These facts are more useful for selection than brand visibility alone.

What market visibility and monthly traffic mean

In the Labelbox vs SuperAnnotate monthly traffic comparison, Labelbox currently shows 1.1M visits and SuperAnnotate shows 406.4K; Labelbox has about 2.7 times the visible traffic of SuperAnnotate, an absolute difference of about 688.7K visits. This reflects visible reach, not feature quality or paid users.

Both tools provide verified traffic details, so monthly trends, visit depth, regions, and acquisition sources can be compared on the same basis.

If public market visibility is an important first-pass criterion, investigate Labelbox first. The final choice should still follow taxonomy, use case, and a real trial because higher traffic does not prove broader capabilities or better workflow fit.

Product positioning, use cases, and roles

Labelbox and SuperAnnotate currently overlap in shared categories: Beschriftung und Workflow-Management; shared tags: Computer Vision, Datenannotation, Datenlabeling, Mensch-in-der-Schleife und Großes Sprachmodell. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.

Labelbox's unique categories/tags are Maschinelles Lernen, KI-Training, maschinelles Lernen, Modellbewertung, Multimodale KI, NLP und Reinforcement Learning; SuperAnnotate's are MLOps, KI-Datenplattform, KI-Trainingsdaten, Dataset-Management, Retrieval-Augmentierte Generierung, RLHF und SFT. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.

What ratings, comments, and favorites can tell you

Labelbox has no verified rating, 0 comments, 87 favorites, and 91 likes;SuperAnnotate has no verified rating, 0 comments, 89 favorites, and 101 likes。

Neither product has enough rating or comment samples for a credible reputation ranking.

Selection guidance by actual need

When to evaluate Labelbox first

Put Labelbox on the priority trial list when the task aligns with “Beschriftung” and especially Maschinelles Lernen, KI-Training, maschinelles Lernen, Modellbewertung, Multimodale KI und NLP. This follows recorded positioning and does not imply unlisted capabilities are absent.

Labelbox also currently records: pricing is freemium, product type is website, 1.1M verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.

When to evaluate SuperAnnotate first

Put SuperAnnotate on the priority trial list when the task aligns with “Beschriftung” and especially MLOps, KI-Datenplattform, KI-Trainingsdaten, Dataset-Management, Retrieval-Augmentierte Generierung und RLHF. This follows recorded positioning and does not imply unlisted capabilities are absent.

SuperAnnotate also currently records: pricing is freemium, product type is website, 406.4K verified monthly visits, no verified user rating. Verify any hard requirement around price, platform, or reach before trial, and do not let sparse review data substitute for testing.

How to validate the recommendation before deciding

The available data describes positioning, public visibility, and community signals, but it cannot prove output quality, speed, integration effort, privacy, or long-term cost in your workflow. Before deciding, run the same representative tasks in Labelbox and SuperAnnotate, then record completion time, accuracy, manual corrections, and the real paid threshold. A like-for-like trial turns this comparison into a defensible adoption decision.

Vergleichs-FAQ

How should I choose between Labelbox and SuperAnnotate?
Compare positioning, pricing, taxonomy, and traffic maturity, then verify the latest details on each official website.
Where does this comparison data come from?
The factual baseline is derived from product, taxonomy, traffic, and community data. Reviewed editorial conclusions show their source and verification date.
What do unknown fields mean?
Unknown means there is not enough reliable evidence; the page does not fill gaps with assumptions.