# fast.ai vs Museum of Models (Rival)

fast.ai records 250,720 monthly visits with -10.4% month-over-month growth and Free pricing. Museum of Models (Rival) records 9,187 monthly visits with -35% growth and Free pricing.

| Metric | [fast.ai](https://openaitools.app/tool/fast-ai) | [Museum of Models (Rival)](https://openaitools.app/tool/rival) |
| :--- | :--- | :--- |
| Website URL | https://www.fast.ai | https://rival.tips |
| Categories | AI Course, Large Language Models (LLMs), AI Developer Tools, AI Research Tool | AI Models, Large Language Models (LLMs), AI Tools Directory |
| Pricing Model | Free | Free |
| Monthly Visits | 250,720 | 9,187 |
| MoM Growth Rate | -10.4% | -35% |
| Primary Market | United States | United States |
| Direct Visits | 136,995 | 3,663 |
| Review Score | 4.8 | 4.4 |
| Saved Count | 4 | 0 |
| Supported Platforms | Website | Website |

## fast.ai

fast.ai began with a simple premise: deep learning should be taught top-down, starting with working code that produces results on day one, and only then unpacking the theory. That approach produced Practical Deep Learning for Coders, one of the most widely followed free courses in the field, aimed at people with programming experience rather than advanced mathematics. Later offerings include From Deep Learning Foundations to Stable Diffusion and the newer How to Solve It With Code, which replaced the traditional course format with a problem-solving platform.

Software is the second pillar. The fastai library layers a high-level, opinionated API on top of PyTorch so that training state-of-the-art models takes a handful of lines, while remaining flexible enough for research. nbdev lets teams develop, document and publish entire Python packages from inside Jupyter notebooks, solving the long-standing friction between notebooks and version control. Both projects are open source and supported by an active community forum and documentation.

Alongside teaching and tooling, fast.ai publishes widely read writing on the societal side of AI, including critiques of how AI power concentrates, debates about AI safety framing, and analysis of education and technology. In late 2024 the organisation announced it was joining Answer.AI, a new kind of R&D lab focused on building practical end-user products from foundational research, while the fast.ai blog and course materials remain freely available.

**Pricing & Plans:** Everything fast.ai produces is free: the courses, the fastai and nbdev libraries, the documentation and the blog. There is no paid tier, though donations and community contributions are welcome.

- **Practical Deep Learning for Coders:** A free, top-down course that gets you training real models immediately and explains the theory as you go, with notebooks and video lessons.
- **How to Solve It With Code:** A newer educational format that teaches iterative, exploration-driven problem solving with an interactive platform, replacing the classic course structure.
- **fastai library for PyTorch:** A high-level API that makes modern deep learning techniques concise and accessible while staying flexible for research work.
- **nbdev:** Develop, test, document and publish complete Python packages directly from Jupyter notebooks, ending the notebook-versus-git conflict.
- **Research and blog:** Long-form articles on AI in society, education, ethics, technical deep dives and attitudes, plus an active community forum.

**Strengths:** Completely free courses, libraries and reading material with no paywall; Top-down teaching style that suits working developers; Backed by production-grade open-source software used well beyond the courses; Independent, critical writing on AI ethics and society alongside technical content

**Limitations:** Teaching style is opinionated, so some learners prefer a theory-first curriculum; Course content evolves gradually and older materials can drift out of date; No formal certification, tutoring or career support is offered

[Profile (Markdown)](https://openaitools.app/tool/fast-ai.md)

## Museum of Models (Rival)

Museum of Models — the project formerly known as Rival — is a free, ad-free archive of how AI models actually answer. Since May 2024, the same 100 questions have been put to every model in the exact same way, once, and every answer has been kept exactly as it was given, including the odd ones and the empty ones. The result is 18,773 answers from 385 models, a record of how each one drew a pelican, built a landing page, told five jokes, or named a favourite city.

The premise is that leaderboards only remember scores. When a lab retires a model and switches it off, its weights often disappear and nobody can ask it anything again. The museum keeps the outputs themselves: 121 of the 385 models featured are no longer served on OpenRouter, yet their drawings, websites, writing and image answers are still here to browse.

Nothing on the site is ranked or scored, and supporting it changes nothing about what it shows. Answers are presented in their native form — drawings as SVG, websites running live in a sandbox, images as pictures, writing as readable pages and voices you can play. Visitors can spin an interactive globe of answers, compare two to four models side by side, sort by release date, lab or question, and step back through a monthly timeline of the museum since it opened. The full collection is downloadable and reusable under CC BY 4.0 with credit.

**Pricing & Plans:** The museum is completely free with no ads. Hosting costs are covered by voluntary donations, such as buying the creator a coffee, and all answer data can be downloaded and reused under CC BY 4.0 with credit.

- **18,773 answers from 385 models:** One hundred identical questions covering drawings, websites, writing, images, code and audio, each answered by every model and kept as given.
- **Retired models preserved:** 121 of the 385 models are no longer served on OpenRouter, yet their answers remain viewable, preserving outputs that would otherwise be lost.
- **Side-by-side comparison:** Add two to four models with a single click and view their answers to the same questions next to each other.
- **Interactive globe and index:** Explore a magnifiable globe of answers, an index sortable by release date, lab or question, a monthly timeline, and a fast command-K search.
- **Live, runnable exhibits:** Generated websites run live in a sandbox, drawings are the model's own SVG, images are shown at 640px, and voices can be played directly.

**Strengths:** Completely free and ad-free, with no login required; Preserves answers from models that have since been retired and switched off; Methodologically consistent: identical prompts, one attempt, documented settings; Open data downloadable under CC BY 4.0 and explorable through globe, index and side-by-side views

[Profile (Markdown)](https://openaitools.app/tool/rival.md)

## Frequently Asked Questions

### How do fast.ai and Museum of Models (Rival) compare in monthly traffic?

fast.ai has 250,720 monthly visits, while Museum of Models (Rival) has 9,187. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

fast.ai has a month-over-month growth rate of -10.4%; Museum of Models (Rival) has -35%.

### How does pricing compare?

fast.ai: Free. Everything fast.ai produces is free: the courses, the fastai and nbdev libraries, the documentation and the blog. There is no paid tier, though donations and community contributions are welcome. Museum of Models (Rival): Free. The museum is completely free with no ads. Hosting costs are covered by voluntary donations, such as buying the creator a coffee, and all answer data can be downloaded and reused under CC BY 4.0 with credit.

## 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 | Offers broad structured courses by Andrew Ng, but lacks fast.ai's deep hands-on focus on PyTorch code. | [.md](https://openaitools.app/tool/deeplearning-ai.md) |
| 2 | [PromptHero](https://openaitools.app/tool/prompthero) | 1,044,654 | -2.4% | Freemium | Search millions of AI prompts and generate images and videos with every major model | [.md](https://openaitools.app/tool/prompthero.md) |
| 3 | [Design Arena](https://openaitools.app/tool/design-arena) | 949,534 | -13.2% | Free | Crowdsourced arena where AI models compete and humans crown the best design output | [.md](https://openaitools.app/tool/design-arena.md) |
| 4 | [OpenAI Academy](https://openaitools.app/tool/openai-academy) | 937,379 | -6.3% | Free | Provides official structured learning resources for AI development, but centers on OpenAI's proprietary ecosystem rather than PyTorch. | [.md](https://openaitools.app/tool/openai-academy.md) |
| 5 | [LabLab.ai](https://openaitools.app/tool/lablab-ai) | 431,529 | -39.7% | Free | Hosts hands-on AI hackathons and developer tutorials, but emphasizes rapid prototyping over deep academic machine learning. | [.md](https://openaitools.app/tool/lablab-ai.md) |
| 6 | [Models.dev](https://openaitools.app/tool/models-dev) | 200,451 | -3.9% | Free | Open-source database of AI models, prices and capabilities | [.md](https://openaitools.app/tool/models-dev.md) |
| 7 | [Learn Prompting](https://openaitools.app/tool/learn-prompting) | 159,807 | -8.6% | Freemium, Free Trial, Contact for Pricing | Offers free educational guides on prompt engineering, but focuses on LLM usage rather than training neural networks. | [.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 | A vibrant open community for data science practitioners, though it operates as a network rather than structured courses. | [.md](https://openaitools.app/tool/ods-ai.md) |
| 9 | [The Full Stack (fullstackdeeplearning.com)](https://openaitools.app/tool/fullstackdeeplearning-com) | 46,082 | +6.6% | Free (educational content) | Provides practical production machine learning tutorials, but covers broader deployment stacks rather than pure deep learning foundations. | [.md](https://openaitools.app/tool/fullstackdeeplearning-com.md) |
| 10 | [All GPTs](https://openaitools.app/tool/all-gpts) | 32,569 | +9.3% | Free | A curated directory of 30,000+ custom GPTs and AI agents | [.md](https://openaitools.app/tool/all-gpts.md) |

---
Source: https://openaitools.app/compare/fast-ai-vs-rival

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