Hugging Face
데이터셋 · 27.4M 월 방문
Hugging Face는 선도적인 오픈소스 머신러닝 플랫폼이자 커뮤니티입니다. 개발자와 연구자가 최첨단 모델을 구축, 훈련 및 배포할 수 있는 도구를 제공하며, 방대한 사전 훈련된 모델, 데이터셋 및 데모 애플리케이션 허브를 제공합니다.
VS
ModelScope
모델 허브 · 2.9M 월 방문
ModelScope는 방대한 모델 및 데이터셋 라이브러리를 제공하는 오픈 소스 AI 모델 커뮤니티 및 플랫폼입니다. 무료 컴퓨팅 리소스가 지원되는 '서비스형 모델'(MaaS) 생태계를 통해 손쉬운 모델 훈련, 추론 및 애플리케이션 개발 도구를 제공합니다.
제품 개요
Hugging Face 제품 개요
Hugging Face는 선도적인 오픈소스 머신러닝 플랫폼이자 커뮤니티입니다. 개발자와 연구자가 최첨단 모델을 구축, 훈련 및 배포할 수 있는 도구를 제공하며, 방대한 사전 훈련된 모델, 데이터셋 및 데모 애플리케이션 허브를 제공합니다.
Preview
ModelScope 제품 개요
ModelScope는 방대한 모델 및 데이터셋 라이브러리를 제공하는 오픈 소스 AI 모델 커뮤니티 및 플랫폼입니다. 무료 컴퓨팅 리소스가 지원되는 '서비스형 모델'(MaaS) 생태계를 통해 손쉬운 모델 훈련, 추론 및 애플리케이션 개발 도구를 제공합니다.
Preview
Detailed feature comparison
| Feature | Hugging Face | ModelScope |
|---|---|---|
| 주요 카테고리 | 데이터셋 | 모델 허브 |
| 등록일 | 2025-08-17 | 2025-08-03 |
| 가격 | 프리미엄 | 프리미엄 |
| 공식 사이트 | huggingface.co | modelscope.cn |
| 제품 유형 | 웹사이트 | 웹사이트 |
| Performance data | ||
| 사용자 평점 | 확인되지 않음 | 확인되지 않음 |
| 댓글 | 0 | 0 |
| 월 방문 | 27.4M | 2.9M |
| 월 성장률 | -9.6% | -26.3% |
| 즐겨찾기 | 117 | 114 |
| Details | 상세 보기 | 상세 보기 |
Hugging Face vs ModelScope monthly traffic
Compare Hugging Face and ModelScope by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the Hugging Face vs ModelScope monthly traffic comparison, Hugging Face currently shows 27.4M visits and ModelScope shows 2.9M; Hugging Face has about 9.4 times the visible traffic of ModelScope, an absolute difference of about 24.4M 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.
ModelScope is registered at the modelscope.cn/home subpage. Because the current data does not state whether other host pages are excluded, treat this as domain-level context rather than independent traffic for one product or project.
Hugging Face monthly traffic:
Latest traffic
월 방문
27.4M
평균 방문 시간
5:18
방문당 페이지
6.47
이탈률
41.95%
Data updated 2026-06-15
Monthly traffic trend
- 2025/9: 22.9M 월 방문
- 2026/1: 24.9M 월 방문
- 2026/2: 23.3M 월 방문
- 2026/3: 26.4M 월 방문
- 2026/4: 30.3M 월 방문
- 2026/5: 27.4M 월 방문
주요 지역
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 38.11% | 10.4M |
| 🇨🇳China | 25.84% | 7.1M |
| 🇮🇳India | 17.44% | 4.8M |
| 🇷🇺Russia | 9.32% | 2.6M |
| 🇩🇪Germany | 9.29% | 2.5M |
트래픽 소스
| Source type | Percentage | Traffic |
|---|---|---|
| 직접 | 79.44% | 21.7M |
| 리퍼럴 | 19.3% | 5.3M |
| 이메일 | 1.26% | 344.8K |
검색 키워드
deepseekdeepseek v4deepseek v4 prohugging facehuggingface
ModelScope monthly traffic:
Latest traffic
월 방문
2.9M
평균 방문 시간
4:55
방문당 페이지
6.81
이탈률
35.01%
Data updated 2026-06-15
Monthly traffic trend
- 2026/1: 2.8M 월 방문
- 2026/2: 2.6M 월 방문
- 2026/3: 3.5M 월 방문
- 2026/4: 4M 월 방문
- 2026/5: 2.9M 월 방문
주요 지역
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇨🇳China | 88.58% | 2.6M |
| 🇺🇸United States | 4.98% | 145.7K |
| 🇭🇰Hong Kong | 4.52% | 132.2K |
| 🇹🇼Taiwan | 1.19% | 34.8K |
| 🇸🇬Singapore | 0.73% | 21.4K |
트래픽 소스
| Source type | Percentage | Traffic |
|---|---|---|
| 직접 | 83.92% | 2.5M |
| 리퍼럴 | 16% | 468.1K |
| 이메일 | 0.08% | 2.3K |
검색 키워드
modelscope魔塔魔塔社区魔搭魔搭社区
Traffic-based selection guidance: If public market visibility is an important first-pass criterion, investigate Hugging Face 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 Hugging Face and ModelScope
Hugging Face Core features
데이터셋
머신러닝
협업
ModelScope Core features
모델 허브
연구
로우 코드 노 코드
Use cases
Hugging Face Use cases
AI 커뮤니티
컴퓨터 비전
대규모 언어 모델
NLP
오픈 소스
데이터셋 호스팅
개발자 플랫폼
확산 모델
기계 학습
모델 허브
ModelScope Use cases
AI 커뮤니티
컴퓨터 비전
대규모 언어 모델
NLP
오픈 소스
AI 개발
알리바바
미세 조정
MaaS
모델 라이브러리
Hugging Face vs ModelScope：In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth Hugging Face vs ModelScope comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. Hugging Face is primarily listed under “데이터셋”, while ModelScope is primarily listed under “모델 허브”, so the first decision is whether your actual task matches their recorded scope.
The structured fields currently show these decision-relevant differences: Primary category (Hugging Face: 데이터셋; ModelScope: 모델 허브); Monthly visits (Hugging Face: 27.4M; ModelScope: 2.9M); Monthly growth (Hugging Face: -9.6%; ModelScope: -26.3%); Favorites (Hugging Face: 117; ModelScope: 114); Website (Hugging Face: huggingface.co; ModelScope: modelscope.cn). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the Hugging Face vs ModelScope monthly traffic comparison, Hugging Face currently shows 27.4M visits and ModelScope shows 2.9M; Hugging Face has about 9.4 times the visible traffic of ModelScope, an absolute difference of about 24.4M 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.
ModelScope is registered at the modelscope.cn/home subpage. Because the current data does not state whether other host pages are excluded, treat this as domain-level context rather than independent traffic for one product or project.
If public market visibility is an important first-pass criterion, investigate Hugging Face 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
Hugging Face and ModelScope currently overlap in shared tags: AI 커뮤니티, 컴퓨터 비전, 대규모 언어 모델, NLP 및 오픈 소스. This can place both on the same shortlist, but it does not prove equal implementation, depth, or cost.
Hugging Face's unique categories/tags are 데이터셋, 머신러닝, 협업, 데이터셋 호스팅, 개발자 플랫폼, 확산 모델, 기계 학습 및 모델 허브; ModelScope's are 모델 허브, 연구, 로우 코드 노 코드, AI 개발, 알리바바, 미세 조정, MaaS 및 모델 라이브러리. 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
Hugging Face has no verified rating, 0 comments, 117 favorites, and 126 likes；ModelScope has no verified rating, 0 comments, 114 favorites, and 118 likes。
Neither product has enough rating or comment samples for a credible reputation ranking.
Selection guidance by actual need
When to evaluate Hugging Face first
Put Hugging Face on the priority trial list when the task aligns with “데이터셋” and especially 데이터셋, 머신러닝, 협업, 데이터셋 호스팅, 개발자 플랫폼 및 확산 모델. This follows recorded positioning and does not imply unlisted capabilities are absent.
Hugging Face also currently records: pricing is freemium, product type is website, 27.4M 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 ModelScope first
Put ModelScope on the priority trial list when the task aligns with “모델 허브” and especially 모델 허브, 연구, 로우 코드 노 코드, AI 개발, 알리바바 및 미세 조정. This follows recorded positioning and does not imply unlisted capabilities are absent.
ModelScope also currently records: pricing is freemium, product type is website, 2.9M monthly visits shown for the registered host (subpage scope unknown), 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 Hugging Face and ModelScope, 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.
비교 FAQ
How should I choose between Hugging Face and ModelScope?
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.