# The Full Stack (fullstackdeeplearning.com) vs Models.dev

The Full Stack (fullstackdeeplearning.com) records 46,082 monthly visits with +6.6% month-over-month growth and Free (educational content) pricing. Models.dev records 200,451 monthly visits with -3.9% growth and Free pricing.

| Metric | [The Full Stack (fullstackdeeplearning.com)](https://openaitools.app/tool/fullstackdeeplearning-com) | [Models.dev](https://openaitools.app/tool/models-dev) |
| :--- | :--- | :--- |
| Website URL | https://fullstackdeeplearning.com | https://models.dev |
| Categories | AI Course, Large Language Models (LLMs), Prompt Engineering, AI Developer Tools | AI Models, AI API, Open Source AI Models, AI Tools Directory |
| Pricing Model | Free (educational content) | Free |
| Monthly Visits | 46,082 | 200,451 |
| MoM Growth Rate | +6.6% | -3.9% |
| Primary Market | United States | China |
| Direct Visits | 26,064 | 136,316 |
| Review Score | 4.6 | 4.4 |
| Saved Count | 1 | 0 |
| Supported Platforms | Website | Website |

## The Full Stack (fullstackdeeplearning.com)

Full Stack Deep Learning began as a course teaching engineers to take deep learning from notebook to production, and it has grown into a broader educational hub. The site hosts complete course materials — lecture pages, slides, lab notebooks, and video walkthroughs — for both its Deep Learning Course and its LLM Bootcamp, so learners can follow along at their own pace without paying for a seat.

The curriculum is deliberately full-stack rather than model-centric. The Deep Learning Course covers development infrastructure, experiment management, troubleshooting and testing, data management and annotation, deployment, continual learning, and model monitoring, plus team and project management and ethics. The LLM Bootcamp goes into prompt engineering, augmented language models, LLMOps, and user experience for language interfaces, and includes build-along project walkthroughs.

Beyond courses, the site publishes a blog, hosts a manifesto on building AI products collaboratively, and maintains reference material such as a cloud GPU pricing guide. Because the materials are released publicly and remain accessible, the site functions as a long-lived library rather than a time-boxed bootcamp, and its audience spans individual developers, teams, and educators looking for structured material.

**Pricing & Plans:** The published course material on fullstackdeeplearning.com is available free of charge. There is no conventional subscription or per-seat pricing listed on the site; the project has historically been supported by sponsors and community interest. Any future paid programs would be announced on the site.

- **Free LLM Bootcamp materials:** Lecture pages and resources covering prompt engineering, augmented language models, LLMOps, and language UI/UX.
- **Full Deep Learning Course archive:** Multi-year course content on infrastructure, data management, deployment, monitoring, and ML team organization.
- **Working with AI Agents:** Current material on collaborating with and building agent-based systems, including a perspective on multiplayer AI.
- **Cloud GPU reference:** A maintained guide to cloud GPU options that helps teams choose compute for training and inference.
- **Blog and community resources:** Articles and updates aimed at practitioners building AI products, with a newsletter to follow new releases.

**Strengths:** Course materials are open and free to follow at your own pace; Covers the full product lifecycle, not just model training; Maintained across multiple years, so it documents how practice evolved; Includes hands-on labs and build-along project walkthroughs

**Limitations:** Some flagship courses date from 2021-2023, so tooling specifics age; Not an interactive cohort programme, so there is no instructor feedback; Sparse on formal certification or structured assessments

[Profile (Markdown)](https://openaitools.app/tool/fullstackdeeplearning-com.md)

## Models.dev

Models.dev exists to answer a very practical developer question: which model should I use, and what will it cost? The site organises every entry under a canonical identifier in the form provider/model, so the same model served by several providers can be compared directly rather than guessed at. Columns cover context window, maximum output, whether input and output are supported, reasoning, tool calling, structured output, temperature control, open versus closed weights, price per million tokens, and release and update dates.

Because model releases move fast, the catalogue is built to stay current, with sortable and searchable tables that let you scan by lab or provider and filter down to what matters. Entries include both closed flagship models and open-weight alternatives, making it useful for cost planning as well as capability research.

The project is open source and free to use, and it is intended to be consumed programmatically. Developers can pull the catalogue into their own tooling through a JSON API or a type-safe SDK, which makes it a practical backend for dashboards, routing logic, or internal cost calculators rather than just a reference page to browse.

**Pricing & Plans:** Models.dev is free and open source. It is a reference database, so the prices it lists are the per-million-token rates charged by the model providers themselves, not a fee for using the site.

- **Canonical model identifiers:** Every model uses a consistent provider/model format so the same model across providers can be compared directly.
- **Specification comparison:** Side-by-side context window, output limit, reasoning, tool calling, structured output, and temperature support.
- **Pricing transparency:** Input and output prices per million tokens listed alongside release and update dates.
- **Open and closed models:** Covers closed flagship APIs and open-weight models from many labs in one sortable catalogue.
- **Developer access:** Consume the catalogue through a JSON API or a type-safe SDK for your own tools and dashboards.

**Strengths:** Free and open source with no account required; Consistent canonical identifiers make cross-provider comparison reliable; Covers pricing, limits, and capabilities in one sortable table; Available as a JSON API and type-safe SDK for programmatic use

**Limitations:** It is a reference catalogue, not an inference or hosting service; Data quality depends on community and maintainer updates keeping pace with releases; Interface is aimed at developers and offers little guidance for non-technical users

[Profile (Markdown)](https://openaitools.app/tool/models-dev.md)

## Frequently Asked Questions

### How do The Full Stack (fullstackdeeplearning.com) and Models.dev compare in monthly traffic?

The Full Stack (fullstackdeeplearning.com) has 46,082 monthly visits, while Models.dev has 200,451. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

The Full Stack (fullstackdeeplearning.com) has a month-over-month growth rate of +6.6%; Models.dev has -3.9%.

### How does pricing compare?

The Full Stack (fullstackdeeplearning.com): Free (educational content). The published course material on fullstackdeeplearning.com is available free of charge. There is no conventional subscription or per-seat pricing listed on the site; the project has historically been supported by sponsors and community interest. Any future paid programs would be announced on the site. Models.dev: Free. Models.dev is free and open source. It is a reference database, so the prices it lists are the per-million-token rates charged by the model providers themselves, not a fee for using the site.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [DeepLearning.AI](https://openaitools.app/tool/deeplearning-ai) | 2,562,512 | -7.2% | Freemium | AI engineering courses, certificates, and the world's biggest AI newsletter | [.md](https://openaitools.app/tool/deeplearning-ai.md) |
| 2 | [The Rundown AI](https://openaitools.app/tool/the-rundown-ai) | 1,018,070 | +28.6% | Free | The top AI news and how to apply it, in five minutes a day | [.md](https://openaitools.app/tool/the-rundown-ai.md) |
| 3 | [OpenAI Academy](https://openaitools.app/tool/openai-academy) | 937,379 | -6.3% | Free | Free courses, live events and community for building real AI skills | [.md](https://openaitools.app/tool/openai-academy.md) |
| 4 | [LabLab.ai](https://openaitools.app/tool/lablab-ai) | 431,529 | -39.7% | Free | Free AI hackathons and a global community for AI builders | [.md](https://openaitools.app/tool/lablab-ai.md) |
| 5 | [fast.ai](https://openaitools.app/tool/fast-ai) | 250,720 | -10.4% | Free | Free practical deep learning courses, research and open-source libraries | [.md](https://openaitools.app/tool/fast-ai.md) |
| 6 | [Stork](https://openaitools.app/tool/stork) | 201,544 | +2.3% | Free | Includes model pricing trackers and developer news alongside tools directories, but less focused on raw API specs. | [.md](https://openaitools.app/tool/stork.md) |
| 7 | [Learn Prompting](https://openaitools.app/tool/learn-prompting) | 159,807 | -8.6% | Freemium, Free Trial, Contact for Pricing | Free open course for prompt engineering and AI security | [.md](https://openaitools.app/tool/learn-prompting.md) |
| 8 | [Open Data Science (ODS.ai)](https://openaitools.app/tool/ods-ai) | 159,630 | +15.9% | Free | Community hub for data science, machine learning and AI practitioners | [.md](https://openaitools.app/tool/ods-ai.md) |
| 9 | [AIToolGo](https://openaitools.app/tool/aitoolgo) | 85,066 | +11.8% | Free | Discover AI tools and learn AI fundamentals in one searchable hub | [.md](https://openaitools.app/tool/aitoolgo.md) |
| 10 | [InfraBase.ai](https://openaitools.app/tool/infrabase-ai) | 39,072 | -13.6% | Free | Catalogues and compares AI infrastructure tools and services across categories, but lacks deep per-token pricing tables. | [.md](https://openaitools.app/tool/infrabase-ai.md) |

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Source: https://openaitools.app/compare/fullstackdeeplearning-com-vs-models-dev

More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)