Appen VS Models.dev
Compare Appen VS Models.dev, what is the difference between Appen and Models.dev?
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Summarize
Appen summarize
Appen Landing Page
Models.dev summarize
Models.dev is a comprehensive open-source database of AI model specifications, pricing, and features.
Models.dev Landing Page
Compare Details
Appen details
| Categories | AI Models, Large Language Models (LLMs), AI Developer Tools |
| Appen Website | https://appen.com?utm_source=toolify |
| Added Time | December 25 2023 |
| Appen Pricing | -- |
Models.dev details
| Categories | AI Models, AI API, Open Source AI Models, AI Tools Directory |
| Models.dev Website | https://models.dev?utm_source=toolify |
| Added Time | September 09 2026 |
| Models.dev Pricing | -- |
Comparison of usage
How to use Appen?
To use Appen, you can explore their platform for data solutions, contact them to speak to an expert about your specific needs, or join their crowd to contribute to data collection and annotation efforts. They offer various services and a platform to help you collect, curate, and fine-tune data for your AI models.
How to use Models.dev?
Browse the Models section to search and compare AI models by provider, laboratory, capabilities, context window, output limit, pricing, and release information. Open an individual model page to view its specifications and the providers offering it, or explore provider and lab pages for broader catalogs. Developers can access the data through the JSON endpoints at models.dev/api.json, models.dev/models.json, and models.dev/catalog.json, or install the @opencode-ai/models SDK for type-safe application integration.
Compare Pros between Appen and Models.dev
Core features of Appen
- AI Training Data
- Data Annotation
- Data Collection
- LLM Training Data & Services
- Multilingual AI
- Evaluation & Benchmarking
- Supervised Fine Tuning
- Off-the-Shelf Datasets
- Platform for data collection and curation
Core features of Models.dev
- Searchable database of AI model specifications and capabilities
- Provider-by-provider pricing and model availability comparisons
- Model pages with context limits, output limits, release dates, weights, and supported features
- Provider pages listing available models
- Laboratory pages grouping canonical models by author
- JSON APIs for model, provider, and combined catalog data
- Type-safe SDK with an offline snapshot
- Provider and laboratory logo resources
Compare Use Cases
Use cases for Appen
- Improving AI model performance through high-quality data
- Building foundation models and enterprise-ready AI applications
- Collecting, curating, and fine-tuning data for AI projects
- Training AI engines for conversational experiences
Use cases for Models.dev
- Compare GPT-6 Astra pricing and capabilities across providers before selecting an API
- Evaluate models by context window, output limit, reasoning, tool calling, and structured output support
- Find open-weight models suitable for self-hosting or research
- Build an application that queries current AI model catalog metadata through the API or SDK
- Research model release histories, providers, and laboratory offerings
Appen's traffic
Appen is the one with 745.1K monthly visits and 00:01:26 Avg.visit duration. Appen has a Page per visit of 3.05 and a bounce rate of 44.80%.
Visit Over Time
| Monthly Visits | 745.1K |
| Avg·visit Duration | 00:01:26 |
| Page per Visit | 3.05 |
| Bounce Rate | 44.80% |
Models.dev's traffic
Models.dev is the one with 250.8K monthly visits and 00:00:37 Avg.visit duration. Models.dev has a Page per visit of 2.50 and a bounce rate of 40.48%.
Visit Over Time
| Monthly Visits | 250.8K |
| Avg·visit Duration | 00:00:37 |
| Page per Visit | 2.50 |
| Bounce Rate | 40.48% |
Geography
The top 5 countries/regions for Appen are:United States 19.05%, India 9.93%, Indonesia 6.19%, Brazil 5.20%, Philippines 4.75%
Top 5 Countries/regions
 | 19.05% |
 | 9.93% |
 | 6.19% |
 | 5.20% |
 | 4.75% |
Geography
The top 5 countries/regions for Models.dev are:China 15.27%, United States 12.90%, Indonesia 6.16%, Singapore 5.42%, Vietnam 4.52%
Top 5 Countries/regions
 | 15.27% |
| 12.90% |
| 6.16% |
 | 5.42% |
 | 4.52% |
Traffic Sources
The 6 main sources of traffic to Appen are:vs_sourcesSearchOrganic 43.51%, Direct 32.19%, Referrals 13.06%, Mail 4.22%, vs_sourcesGenAi 3.14%, vs_sourcesSocialOrganic 2.69%, vs_sourcesSearchPaid 0.60%, vs_sourcesSocialPaid 0.34%, vs_sourcesDisplayAds 0.19%, vs_sourcesAffiliate 0.06%
vs_sourcesSearchOrganic | 43.51% |
Direct | 32.19% |
Referrals | 13.06% |
Mail | 4.22% |
vs_sourcesGenAi | 3.14% |
vs_sourcesSocialOrganic | 2.69% |
vs_sourcesSearchPaid | 0.60% |
vs_sourcesSocialPaid | 0.34% |
vs_sourcesDisplayAds | 0.19% |
vs_sourcesAffiliate | 0.06% |
Traffic Sources
The 6 main sources of traffic to Models.dev are:Direct 65.70%, Referrals 17.32%, vs_sourcesSearchOrganic 10.09%, vs_sourcesSocialOrganic 3.19%, vs_sourcesGenAi 2.14%, vs_sourcesDisplayAds 0.98%, Mail 0.58%, vs_sourcesAffiliate 0.00%, vs_sourcesSearchPaid 0.00%, vs_sourcesSocialPaid 0.00%
Direct | 65.70% |
Referrals | 17.32% |
vs_sourcesSearchOrganic | 10.09% |
vs_sourcesSocialOrganic | 3.19% |
vs_sourcesGenAi | 2.14% |
vs_sourcesDisplayAds | 0.98% |
Mail | 0.58% |
vs_sourcesAffiliate | 0.00% |
vs_sourcesSearchPaid | 0.00% |
vs_sourcesSocialPaid | 0.00% |
Which is better: Appen or Models.dev?
Appen might be a bit more popular than Models.dev.As you can see, Appen has 745.1K monthly visits, while Models.dev has 250.8K monthly visits. So more people choose Appen. So the odds are that people will recommend Appen more on social platforms.
Appen has an Avg.visit duration of 00:01:26, while Models.dev has an Avg.visit duration of 00:00:37. Also, Appen has a page per visit of 3.05 and a Bounce Rate of 44.80%. Models.dev has a page per visit of 2.50 and a Bounce Rate of 40.48%.
The main users of Appen are United States, India, Indonesia, Brazil, Philippines, with the following distribution: 19.05%, 9.93%, 6.19%, 5.20%, 4.75%.
The main users of Models.dev are China, United States, Indonesia, Singapore, Vietnam, with the following distribution: 15.27%, 12.90%, 6.16%, 5.42%, 4.52%.
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