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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Microsoft Open Source
プラットフォーム · 210K 月間訪問数
Microsoftの広範なオープンソースプロジェクトのポートフォリオを発見、利用、貢献するための中央ハブ。開発者に強力なツール、フレームワーク、AI/MLライブラリへのアクセスを提供し、グローバルコミュニティ内での協力と革新を促進します。
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
Microsoft Open Source 製品概要
Microsoftの広範なオープンソースプロジェクトのポートフォリオを発見、利用、貢献するための中央ハブ。開発者に強力なツール、フレームワーク、AI/MLライブラリへのアクセスを提供し、グローバルコミュニティ内での協力と革新を促進します。
Preview
Detailed feature comparison
| Feature | Hugging Face | Microsoft Open Source |
|---|---|---|
| 主要カテゴリー | データセット | プラットフォーム |
| 追加日 | 2025-08-17 | 2025-08-01 |
| 価格 | フリーミアム | 無料 |
| 公式サイト | huggingface.co | opensource.microsoft.com |
| 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 | 210K |
| 月間成長率 | -9.6% | 50.5% |
| お気に入り | 117 | 106 |
| Details | 詳細を見る | 詳細を見る |
Hugging Face vs Microsoft Open Source monthly traffic
Compare Hugging Face and Microsoft Open Source by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the Hugging Face vs Microsoft Open Source monthly traffic comparison, Hugging Face currently shows 27.4M visits and Microsoft Open Source shows 210K; Hugging Face has about 130.3 times the visible traffic of Microsoft Open Source, an absolute difference of about 27.2M 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.
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
Microsoft Open Source monthly traffic:
Latest traffic
月間訪問数
210K
平均滞在時間
1:01
訪問あたりページ数
1.94
直帰率
63.86%
Data updated 2026-06-15
Monthly traffic trend
- 2025/9: 137.2K 月間訪問数
- 2026/1: 72.4K 月間訪問数
- 2026/2: 73.7K 月間訪問数
- 2026/3: 117.3K 月間訪問数
- 2026/4: 139.5K 月間訪問数
- 2026/5: 210K 月間訪問数
主要地域
Top 5 countries/regions
| Country/region | Percentage | Traffic |
|---|---|---|
| 🇺🇸United States | 54.77% | 115K |
| 🇮🇳India | 16.45% | 34.5K |
| 🇯🇵Japan | 9.88% | 20.7K |
| 🇨🇦Canada | 9.6% | 20.2K |
| 🇬🇧United Kingdom | 9.3% | 19.5K |
流入元
| Source type | Percentage | Traffic |
|---|---|---|
| 参照元 | 50.87% | 106.8K |
| ダイレクト | 48.22% | 101.3K |
| Eメール | 0.91% | 1.9K |
検索キーワード
agent governance toolkitagent os kernelazure linux 4.0microsoft agent governance toolkitversions of basic still available
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 Microsoft Open Source
Hugging Face Core features
コラボレーション
データセット
機械学習
Microsoft Open Source Core features
コラボレーション
プラットフォーム
機械学習
コードリポジトリ
Use cases
Hugging Face Use cases
機械学習
オープンソース
AIコミュニティ
コンピュータビジョン
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
大規模言語モデル
モデルハブ
NLP
Microsoft Open Source Use cases
機械学習
オープンソース
AI
アジュール
コーディング
コラボレーション
開発者ツール
フレームワーク
GitHub
ライブラリ
マイクロソフト
.NET
vscode
Hugging Face vs Microsoft Open Source：In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth Hugging Face vs Microsoft Open Source 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 Microsoft Open Source is primarily listed under “プラットフォーム”, 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; Microsoft Open Source: プラットフォーム); Pricing (Hugging Face: Freemium; Microsoft Open Source: Free); Monthly visits (Hugging Face: 27.4M; Microsoft Open Source: 210K); Monthly growth (Hugging Face: -9.6%; Microsoft Open Source: 50.5%); Favorites (Hugging Face: 117; Microsoft Open Source: 106). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the Hugging Face vs Microsoft Open Source monthly traffic comparison, Hugging Face currently shows 27.4M visits and Microsoft Open Source shows 210K; Hugging Face has about 130.3 times the visible traffic of Microsoft Open Source, an absolute difference of about 27.2M 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 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 Microsoft Open Source currently overlap in shared categories: コラボレーション; shared tags: 機械学習、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、AIコミュニティ、コンピュータビジョン、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、大規模言語モデル; Microsoft Open Source's are プラットフォーム、機械学習、コードリポジトリ、AI、アジュール、コーディング、コラボレーション、開発者ツール. 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；Microsoft Open Source has no verified rating, 0 comments, 106 favorites, and 102 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、AIコミュニティ、コンピュータビジョン、データセットホスティング、開発者プラットフォーム. 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 Microsoft Open Source first
Put Microsoft Open Source on the priority trial list when the task aligns with “プラットフォーム” and especially プラットフォーム、機械学習、コードリポジトリ、AI、アジュール、コーディング. This follows recorded positioning and does not imply unlisted capabilities are absent.
Microsoft Open Source also currently records: pricing is free, product type is website, 210K 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 Hugging Face and Microsoft Open Source, 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 Microsoft Open Source?
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.