Hugging Face
データセット · 27.4M 月間訪問数
Hugging Faceは、主要なオープンソースの機械学習プラットフォームおよびコミュニティです。開発者や研究者が最先端のモデルを構築、トレーニング、デプロイするためのツールを提供し、膨大な事前学習済みモデル、データセット、デモアプリケーションのハブを提供します。
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ModelScope
モデルハブ · 2.9M 月間訪問数
ModelScopeは、膨大なモデルとデータセットのライブラリを提供するオープンソースのAIモデルコミュニティおよびプラットフォームです。無料のコンピューティングリソースに支えられた「Model-as-a-Service」（MaaS）エコシステムにより、簡単なモデルトレーニング、推論、アプリケーション開発ツールを提供します。
製品概要
Hugging Face 製品概要
Hugging Faceは、主要なオープンソースの機械学習プラットフォームおよびコミュニティです。開発者や研究者が最先端のモデルを構築、トレーニング、デプロイするためのツールを提供し、膨大な事前学習済みモデル、データセット、デモアプリケーションのハブを提供します。
Preview
ModelScope 製品概要
ModelScopeは、膨大なモデルとデータセットのライブラリを提供するオープンソースのAIモデルコミュニティおよびプラットフォームです。無料のコンピューティングリソースに支えられた「Model-as-a-Service」（MaaS）エコシステムにより、簡単なモデルトレーニング、推論、アプリケーション開発ツールを提供します。
Preview
Detailed feature comparison
| Feature | Hugging Face | ModelScope |
|---|---|---|
| 主要カテゴリー | データセット | モデルハブ |
| 追加日 | 2025-08-17 | 2025-08-03 |
| 価格 | フリーミアム | フリーミアム |
| 公式サイト | huggingface.co | modelscope.cn |
| 製品タイプ | ウェブサイト | ウェブサイト |
| Performance data | ||
| ユーザー評価 | 未確認 | 未確認 |
| コメント | 0 | 0 |
| 月間訪問数 | 27.4M | 2.9M |
| 月間成長率 | -9.6% | -26.3% |
| お気に入り | 117 | 114 |
| Details | 詳細を見る | 詳細を見る |
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
月間訪問数
27.4M
平均滞在時間
5:18
訪問あたりページ数
6.47
直帰率
41.95%
Data updated 2026-06-15
Monthly traffic trend
- 2025/9: 22.9M 月間訪問数
- 2026/1: 24.9M 月間訪問数
- 2026/2: 23.3M 月間訪問数
- 2026/3: 26.4M 月間訪問数
- 2026/4: 30.3M 月間訪問数
- 2026/5: 27.4M 月間訪問数
主要地域
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 |
流入元
| Source type | Percentage | Traffic |
|---|---|---|
| ダイレクト | 79.44% | 21.7M |
| 参照元 | 19.3% | 5.3M |
| Eメール | 1.26% | 344.8K |
検索キーワード
deepseekdeepseek v4deepseek v4 prohugging facehuggingface
ModelScope monthly traffic:
Latest traffic
月間訪問数
2.9M
平均滞在時間
4:55
訪問あたりページ数
6.81
直帰率
35.01%
Data updated 2026-06-15
Monthly traffic trend
- 2026/1: 2.8M 月間訪問数
- 2026/2: 2.6M 月間訪問数
- 2026/3: 3.5M 月間訪問数
- 2026/4: 4M 月間訪問数
- 2026/5: 2.9M 月間訪問数
主要地域
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 |
流入元
| Source type | Percentage | Traffic |
|---|---|---|
| ダイレクト | 83.92% | 2.5M |
| 参照元 | 16% | 468.1K |
| Eメール | 0.08% | 2.3K |
検索キーワード
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
データセット
機械学習
コラボレーション
ModelScope Core features
モデルハブ
研究
ローコード・ノーコード
Use cases
Hugging Face Use cases
AIコミュニティ
コンピュータビジョン
大規模言語モデル
NLP
オープンソース
データセットホスティング
開発者プラットフォーム
拡散モデル
機械学習
モデルハブ
ModelScope Use cases
AIコミュニティ
コンピュータビジョン
大規模言語モデル
NLP
オープンソース
AI開発
アリババ
ファインチューニング
MaaS
モデルライブラリ
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 “データセット”, while ModelScope is primarily listed under “モデルハブ”, 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: データセット; ModelScope: モデルハブ); 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コミュニティ、コンピュータビジョン、大規模言語モデル、NLP、オープンソース. 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 データセット、機械学習、コラボレーション、データセットホスティング、開発者プラットフォーム、拡散モデル、モデルハブ; ModelScope's are モデルハブ、研究、ローコード・ノーコード、AI開発、アリババ、ファインチューニング、MaaS、モデルライブラリ. 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 “データセット” and especially データセット、機械学習、コラボレーション、データセットホスティング、開発者プラットフォーム、拡散モデル. 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 “モデルハブ” and especially モデルハブ、研究、ローコード・ノーコード、AI開発、アリババ、ファインチューニング. 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.
比較 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.