# fast.ai vs Grably

fast.ai records 250,720 monthly visits with -10.4% month-over-month growth and Free pricing. Grably records 1,923 monthly visits with -13% growth and Contact for Pricing pricing.

| Metric | [fast.ai](https://openaitools.app/tool/fast-ai) | [Grably](https://openaitools.app/tool/grably) |
| :--- | :--- | :--- |
| Website URL | https://www.fast.ai | https://grably.us |
| Categories | AI Course, Large Language Models (LLMs), AI Developer Tools, AI Research Tool | AI Developer Tools, AI Image Recognition, Large Language Models (LLMs) |
| Pricing Model | Free | Contact for Pricing |
| Monthly Visits | 250,720 | 1,923 |
| MoM Growth Rate | -10.4% | -13% |
| Primary Market | United States | Global |
| Direct Visits | 136,995 | 683 |
| Review Score | 4.8 | 3.8 |
| Saved Count | 4 | 1 |
| 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)

## Grably

Grably is a multi-modal human interaction data research company. Rather than selling generic web scrapes, it positions itself as a lab that captures and models how people act, sense, decide, and communicate, then packages that into structured datasets for AI developers. Its site highlights backing from Techstars and partnerships with leading AI labs and technology companies.

The company organizes its offering into suites for image, video, audio, code, and text, alongside a catalogue of multi-modal conversational data. Publicly described assets include billions of sequential messages in more than 100 languages, thousands of hours of labelled sports footage, and tens of millions of medical studies. Each dataset is aimed at a specific modelling need, from LLM pretraining and multilingual coverage to embodied AI, temporal video understanding, speech, and document intelligence.

Grably also builds custom datasets for clients with niche goals, aligning anonymization, filtering, and delivery formats to internal research, legal, and infrastructure requirements. Delivery timelines vary by modality, and pricing is scoped per engagement, so prospective buyers discuss requirements directly with the team. The overall pitch is data quality and human-centred signal, not volume alone.

**Pricing & Plans:** Pricing is contact-based. Each dataset or custom project is quoted according to scope, modalities, and delivery requirements.

- **Multi-modal data suites:** Datasets covering image, video, audio, code, text, and conversational interaction for varied model-training needs.
- **Custom dataset design:** Buyer-scoped datasets with configurable anonymization, filtering, modalities, and delivery formats.
- **Multilingual coverage:** Conversational and text data spanning 100+ languages, including low-resource and underrepresented regions.
- **Structured, annotated content:** Signals that are aligned, annotated, and validated for cross-modality and scientific consistency.
- **Domain-specific corpora:** Specialized datasets for sports, medical records, documents, scientific literature, and code.

**Strengths:** Broad multi-modal and multilingual dataset catalogue; Custom dataset design with configurable anonymization; Enterprise and research-lab oriented delivery; Backed by a recognised accelerator program

**Limitations:** No self-serve pricing or instant purchase flow; Dataset access requires a sales conversation; Delivery timelines for rich modalities can span weeks

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

## Frequently Asked Questions

### How do fast.ai and Grably compare in monthly traffic?

fast.ai has 250,720 monthly visits, while Grably has 1,923. 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%; Grably has -13%.

### 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. Grably: Contact for Pricing. Pricing is contact-based. Each dataset or custom project is quoted according to scope, modalities, and delivery requirements.

## 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 | [clickworker](https://openaitools.app/tool/clickworker-com) | 1,861,149 | +0.5% | Contact for Pricing | Crowdsourcing data services for AI training and market data | [.md](https://openaitools.app/tool/clickworker-com.md) |
| 3 | [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) |
| 4 | [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) |
| 5 | [Surge AI](https://openaitools.app/tool/surgehq-ai) | 245,142 | +6.6% | Contact for Pricing | Expert human data and evaluation for training frontier AI | [.md](https://openaitools.app/tool/surgehq-ai.md) |
| 6 | [Wirestock](https://openaitools.app/tool/wirestock) | 167,156 | +12.9% | Freemium | Where creators get paid and AI teams get premium training data | [.md](https://openaitools.app/tool/wirestock.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 | [huntr](https://openaitools.app/tool/huntr-com) | 45,283 | -61.9% | Free | The bug bounty platform built for AI and ML security | [.md](https://openaitools.app/tool/huntr-com.md) |

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

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