Hugging Face is the leading open-source platform and community for machine learning. It provides tools for developers and researchers to build, train, and deploy state-of-the-art models, offering a vast hub of pre-trained models, datasets, and demo applications.
ModelScope is an open-source AI model community and platform, offering a vast library of models and datasets. It provides a "Model-as-a-Service" (MaaS) ecosystem with tools for easy model training, inference, and application development, supported by free computing resources.
Hugging Face is the leading open-source platform and community for machine learning. It provides tools for developers and researchers to build, train, and deploy state-of-the-art models, offering a vast hub of pre-trained models, datasets, and demo applications.
ModelScope is an open-source AI model community and platform, offering a vast library of models and datasets. It provides a "Model-as-a-Service" (MaaS) ecosystem with tools for easy model training, inference, and application development, supported by free computing resources.
| Feature | Hugging Face | ModelScope |
|---|---|---|
| Primary category | Dataset | Model Hub |
| Added | 2025-08-17 | 2025-08-03 |
| Pricing | Freemium | Freemium |
| Official website | huggingface.co | modelscope.cn |
| Product type | Website | Website |
| Performance data | ||
| User rating | Not verified | Not verified |
| Comments | 0 | 0 |
| Monthly visits | 27.4M | 2.9M |
| Monthly growth | -9.6% | -26.3% |
| Favorites | 117 | 114 |
| Details | View details | View details |
Compare Hugging Face and ModelScope by monthly reach, traffic trend, visit depth, top regions, and acquisition sources.
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.
| 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 |
| Source type | Percentage | Traffic |
|---|---|---|
| Direct | 79.44% | 21.7M |
| Referral | 19.3% | 5.3M |
| 1.26% | 344.8K |
| 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 |
| Source type | Percentage | Traffic |
|---|---|---|
| Direct | 83.92% | 2.5M |
| Referral | 16% | 468.1K |
| 0.08% | 2.3K |
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 “Dataset”, while ModelScope is primarily listed under “Model Hub”, 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: Dataset; ModelScope: Model Hub); 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.
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.
Hugging Face and ModelScope currently overlap in shared tags: AI community, computer vision, large language models, NLP, and open source. 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 Dataset, Machine Learning, Collaboration, dataset hosting, developer platform, diffusion models, machine learning, and model hub; ModelScope's are Model Hub, Research, Low Code No Code, AI development, alibaba, fine-tuning, MaaS, and model library. These unique fields are the strongest differentiators: validate the product whose recorded scope matches the task instead of following traffic alone.
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.
Put Hugging Face on the priority trial list when the task aligns with “Dataset” and especially Dataset, Machine Learning, Collaboration, dataset hosting, developer platform, and diffusion models. 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.
Put ModelScope on the priority trial list when the task aligns with “Model Hub” and especially Model Hub, Research, Low Code No Code, AI development, alibaba, and fine-tuning. 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.
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.
