dataset.gold
データセット · 3.4K 月間訪問数
AIと機械学習のための高品質なオープンソースデータセットのキュレーションされたディレクトリ。コンピュータビジョンやNLPなどのモデルを訓練するための、データのゴールドスタンダードを発見してください。
VS
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
dataset.gold 製品概要
AIと機械学習のための高品質なオープンソースデータセットのキュレーションされたディレクトリ。コンピュータビジョンやNLPなどのモデルを訓練するための、データのゴールドスタンダードを発見してください。
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 | dataset.gold | ModelScope |
|---|---|---|
| 主要カテゴリー | データセット | モデルハブ |
| 追加日 | 2025-08-04 | 2025-08-03 |
| 価格 | 無料 | フリーミアム |
| 公式サイト | dataset.gold | 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 | 3.4K | 2.9M |
| 月間成長率 | 未確認 | -26.3% |
| お気に入り | 118 | 114 |
| Details | 詳細を見る | 詳細を見る |
dataset.gold vs ModelScope monthly traffic
Compare dataset.gold and ModelScope by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
How to interpret the traffic data
In the dataset.gold vs ModelScope monthly traffic comparison, dataset.gold currently shows 3.4K visits and ModelScope shows 2.9M; ModelScope has about 862.8 times the visible traffic of dataset.gold, an absolute difference of about 2.9M visits. This reflects visible reach, not feature quality or paid users.
Only ModelScope has complete third-party traffic details; dataset.gold uses visits recorded inside ToolMage. These scopes cannot estimate market share directly, and on-site views should not be treated as the product’s total website traffic.
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.
dataset.gold monthly traffic:
Latest traffic
月間訪問数
3.4K
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: ModelScope is registered under a modelscope.cn subpath, so its large visible total may include the host platform. The current data does not justify choosing ModelScope for traffic alone; shortlist by unique taxonomy and use case, then validate with the same tasks.
Usage comparison
Compare the core capabilities of dataset.gold and ModelScope
dataset.gold Core features
研究
データセット
機械学習
ModelScope Core features
研究
モデルハブ
ローコード・ノーコード
Use cases
dataset.gold Use cases
コンピュータビジョン
NLP
オープンソース
AIトレーニング
データ収集
データサイエンス
データセット
開発者ツール
機械学習
研究
ModelScope Use cases
コンピュータビジョン
NLP
オープンソース
AIコミュニティ
AI開発
アリババ
ファインチューニング
大規模言語モデル
MaaS
モデルライブラリ
dataset.gold vs ModelScope：In-depth comparison and selection guidance
First decide whether the products solve the same kind of need
This in-depth dataset.gold vs ModelScope comparison uses only the product records, taxonomy, audience, traffic, and community signals available on this page. dataset.gold 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 (dataset.gold: データセット; ModelScope: モデルハブ); Pricing (dataset.gold: Free; ModelScope: Freemium); Monthly visits (dataset.gold: 3.4K; ModelScope: 2.9M); Favorites (dataset.gold: 118; ModelScope: 114); Website (dataset.gold: dataset.gold; ModelScope: modelscope.cn). These facts are more useful for selection than brand visibility alone.
What market visibility and monthly traffic mean
In the dataset.gold vs ModelScope monthly traffic comparison, dataset.gold currently shows 3.4K visits and ModelScope shows 2.9M; ModelScope has about 862.8 times the visible traffic of dataset.gold, an absolute difference of about 2.9M visits. This reflects visible reach, not feature quality or paid users.
Only ModelScope has complete third-party traffic details; dataset.gold uses visits recorded inside ToolMage. These scopes cannot estimate market share directly, and on-site views should not be treated as the product’s total website traffic.
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.
ModelScope is registered under a modelscope.cn subpath, so its large visible total may include the host platform. The current data does not justify choosing ModelScope for traffic alone; shortlist by unique taxonomy and use case, then validate with the same tasks.
Product positioning, use cases, and roles
dataset.gold and ModelScope currently overlap in shared categories: 研究; shared tags: コンピュータビジョン、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.
dataset.gold's unique categories/tags are データセット、機械学習、AIトレーニング、データ収集、データサイエンス、開発者ツール、研究; ModelScope's are モデルハブ、ローコード・ノーコード、AIコミュニティ、AI開発、アリババ、ファインチューニング、大規模言語モデル、MaaS. 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
dataset.gold has no verified rating, 0 comments, 118 favorites, and 114 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 dataset.gold first
Put dataset.gold 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トレーニング、データ収集、データサイエンス、開発者ツール. This follows recorded positioning and does not imply unlisted capabilities are absent.
dataset.gold also currently records: pricing is free, product type is website, 3.4K on-site monthly views, 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、ローコード・ノーコード、AIコミュニティ、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 dataset.gold 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 dataset.gold 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.