A curated directory of high-quality, open-source datasets for AI and machine learning. Discover the gold standard of data for training your models in computer vision, NLP, and more.
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.
Product overview
dataset.gold Product overview
A curated directory of high-quality, open-source datasets for AI and machine learning. Discover the gold standard of data for training your models in computer vision, NLP, and more.
ModelScope Product overview
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.
Detailed feature comparison
| Feature | dataset.gold | ModelScope |
|---|---|---|
| Primary category | Datasets | Model Hub |
| Added | 2025-08-04 | 2025-08-03 |
| Pricing | Free | Freemium |
| Official website | dataset.gold | modelscope.cn |
| Product type | Website | Website |
| Performance data | ||
| User rating | Not verified | Not verified |
| Comments | 0 | 0 |
| Monthly visits | 3.4K | 2.9M |
| Monthly growth | Not verified | -26.3% |
| Favorites | 118 | 114 |
| Details | View details | View details |
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
ModelScope monthly traffic:
Latest traffic
Monthly traffic trend
- 2026/1: 2.8M Monthly visits
- 2026/2: 2.6M Monthly visits
- 2026/3: 3.5M Monthly visits
- 2026/4: 4M Monthly visits
- 2026/5: 2.9M Monthly visits
Top regions
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 |
Traffic sources
| Source type | Percentage | Traffic |
|---|---|---|
| Direct | 83.92% | 2.5M |
| Referral | 16% | 468.1K |
| 0.08% | 2.3K |
Search keywords
Usage comparison
Compare the core capabilities of dataset.gold and ModelScope
dataset.gold Core features
ModelScope Core features
Use cases
dataset.gold Use cases
ModelScope Use cases
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 “Datasets”, 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 (dataset.gold: Datasets; ModelScope: Model Hub); 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: Research; shared tags: computer vision, NLP, and open source. 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 Datasets, Machine Learning, AI training, data collection, data science, dataset, developer tools, and machine learning; ModelScope's are Model Hub, Low Code No Code, AI community, AI development, alibaba, fine-tuning, large language models, and 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 “Datasets” and especially Datasets, Machine Learning, AI training, data collection, data science, and dataset. 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 “Model Hub” and especially Model Hub, Low Code No Code, AI community, 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.
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.
Comparison FAQ
How should I choose between dataset.gold and ModelScope?
Where does this comparison data come from?
What do unknown fields mean?
Related AI tools

Hugging Face
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.
Dataset
Fast.ai
Fast.ai is a research institute dedicated to making deep learning accessible to everyone. It offers free courses, an open-source software library (fastai), cutting-edge research, and a vibrant community, empowering coders of all backgrounds to become deep learning practitioners.
Machine Learning
Label Studio
Label Studio is a versatile open-source data labeling platform designed for a wide range of data types. It enables users to annotate images, text, audio, video, and time-series data to fine-tune LLMs, prepare training data for machine learning, and validate AI models with human-in-the-loop feedback.
Training Data
Google Research
Google Research is a premier hub for exploring groundbreaking advancements in science and AI. It provides open access to a vast repository of research papers, project showcases, and open-source resources across diverse fields like machine learning, quantum computing, and healthcare. It's an essential platform for researchers, developers, and enthusiasts to stay at the forefront of technological innovation and understand its real-world impact.
Learning Platform
TensorFlow
TensorFlow is an end-to-end open-source platform for machine learning developed by Google. It provides a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers and developers build and deploy ML-powered applications. From beginners to experts, TensorFlow offers intuitive high-level APIs for easy model building and powerful low-level APIs for advanced research, enabling deployment across servers, edge devices, and browsers.
Frameworks
MindSpore
MindSpore is an open-source, all-scenario AI computing framework designed for developers and data scientists. It provides a developer-friendly experience with flexible deployment across cloud, edge, and device environments. It excels in distributed training for large models and offers specialized toolkits for scientific computing (AI4S), ensuring high performance and efficiency, especially on Ascend hardware.
Scientific Computing
gts.ai
GTS.ai is a leading AI data solutions provider with over 25 years of experience. They offer high-quality, customized datasets for machine learning, including image, video, speech, and text data. Leveraging a global workforce of over 4.5 million, GTS provides comprehensive services from data collection and annotation to transcription and data management. They ensure data accuracy, security (ISO, GDPR, HIPAA compliant), and scalability for AI projects across various industries, helping businesses propel their AI initiatives forward with reliable data.
Data Annotation
LAION
LAION (Large-scale Artificial Intelligence Open Network) is a non-profit organization dedicated to democratizing AI research. It provides massive, open-source datasets, pre-trained models, and tools to the public, fostering open research, education, and resource-efficient development in machine learning.
Datasets
Width.ai
Width.ai is a specialized AI and machine learning consulting firm that provides custom solutions for businesses. They leverage cutting-edge technologies like GPT, NLP, and computer vision to solve complex problems, automate workflows, and drive growth. Their services range from developing advanced summarizers and chatbots to building high-accuracy product categorization and computer vision systems.
Ai Consulting
PyTorch
PyTorch is an open-source machine learning framework based on the Torch library, used for applications such as computer vision and natural language processing. It offers a flexible, Python-first environment that accelerates the path from research prototyping to production deployment.
Deep Learning
AI Superior
AI Superior is a German-based AI development and consulting company offering end-to-end custom AI solutions. They specialize in computer vision, NLP, predictive analytics, and generative AI for various industries, leveraging a team of PhD-level experts to transform business challenges into scalable, data-driven applications.
Ai Consulting
Labelbox
Labelbox is a comprehensive data-centric AI platform, or "Data Factory," designed for AI teams. It provides integrated software, expert services, and a talent marketplace to create, manage, and evaluate high-quality training data for advanced AI models, including LLMs and multimodal systems.
Labeling
Label Your Data
A professional data annotation service and platform providing high-quality, accurate labeled datasets for machine learning. It supports diverse data types like images, video, text, and audio, offering flexible pricing, a self-serve platform, and fully managed services to scale AI projects of any size.
Data Management
Prodigy
Prodigy is a scriptable annotation tool for AI, Machine Learning, and NLP, designed for developers. It enables rapid creation of high-quality training and evaluation data through model-assisted, human-in-the-loop workflows. It runs on your own infrastructure, ensuring complete data privacy and control.
Annotation
People For AI
People For AI provides expert-driven data labeling services for machine learning projects. They specialize in high-quality, secure annotation for complex image and text datasets. By using in-house, long-term labelers instead of crowdsourcing, they ensure superior accuracy, flexibility, and data security. Their services cater to various industries, including autonomous vehicles, microscopy, retail, and infrastructure, helping companies accelerate their AI development by delivering reliable training data.
Training Data



