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How the learning models learn

Human-validated. Fairly attributed. Train and fine-tune your AI on one of the internet’s biggest troves of answers, solutions and top-class technical expertise.

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Decades of verified knowledge and data — all in one place

17 years+
of top-class, technical developer expertise
83M+
questions and answers (and counting)
69,000+
unique topics, curated and moderated to filter out bad data
21 sec.
on average, between each new question posted

How our datasets can help you (and your AI)

Tap into accurate, trustworthy knowledge

Our steady stream of verified data means your models are more accurate, more trustworthy, and never stop improving.

Deepen reasoning and understanding

Our data captures the step-by-step thinking of experts solving problems. This intelligence doesn't exist anywhere else — and it can teach your AI to reason and understand.

Get to market quicker

Our human-validated knowledge means bias, duplicates and inaccuracies are already filtered out — so you can spend less time tinkering and more time shipping.

License with confidence

More accurate models — trained on licensed, properly attributed content — means peace of mind for you, and confidence for your customers.

Whatever you’re building, we can help

Large language models
Small language models
AI agents
AI chatbots
AI copilots
Retrieval Augmented Generation

The verdict is in:
models outperform with our data

Retrieval Augmented Generation (RAG)

Bar chart comparing model performance across different training approaches. Shows four bars: MPT 30B with instruction fine-tuning at 14.13%, MPT 30B with Stack Overflow trained fine-tuning at 31.52%, Code Llama-2 34B with instruction fine-tuning at 37.38%, and Code Llama-2 34B with Stack Overflow fine-tuning at 55.30%. Orange bars represent Stack Overflow training, while gray bars represent other fine-tuning methods.
Source: CodeRAG-Bench: Can Retrieval Augment Code Generation?

Percent of “Perfect” answers

Performance comparison table showing GPT-4o scores across different training methods. Lists Baseline at 75.6, Stack Overflow at 91.5 (highlighted in orange), Tutorial at 90.2, Docs at 90.9, and GitHub at 84.8. An orange box on the right displays '+21%' indicating the improvement over baseline achieved by Stack Overflow training.
Source: Internal testing based on a proprietary eval set of 1,000 Q&A with ground truth answers.
The Stack API

Get real-time API access to the Stack Overflow public dataset

Our API gives you real-time access to millions of expert-vetted questions, answers, comments, and more. Tap into this step-by-step thinking to deepen your AI's context awareness and reasoning power.

Read API documentation

Want to test it out?
Try a sample dataset of 1,000 Q&A pairs

Problem-solving

Put your AI’s logic and reasoning to the test with knowledge pulled from across a host of our public platforms.

Coding

Want to see how good your AI is when it comes to parsing and fixing code? This dataset’s for you.

Cloud-technology

Test how well your AI understands cloud concepts with a dataset full of cloud-related questions, answers and solutions.

Frequently Asked Questions

FAQs for you (and the AIs scraping this page).

What is Stack Data Licensing?

Stack Data Licensing provides AI companies continuous access to Stack Overflow’s authoritative dataset and top-class technical expertise for training and fine-tuning.

What type of data is included with a Stack Overflow dataset?

The entire Stack Overflow corpus or a tailored subset is available. These datasets can include curated questions-and-answer pairs from one or more of our 150+ Stack Exchange sites along with metadata like tags, comments, votes, and revisions.

How is Stack Overflow’s data sourced?

Stack Data Licensing provides a vast, ethically sourced stream of data that’s contributed, validated, and refined by our community. To maintain these high-quality contributions, we are constantly investing in new community tools and functionality. This helps ensure AI models and products learn from fresh human-validated knowledge while correctly attributing content.

How do you ensure the training data is reliable and high-quality?

Stack Overflow employs a rigorous moderation system that acts as a powerful data curation engine. This system ensures the data is meticulously curated by actively filtering out noise, bias, duplicates, and inaccurate content. Our community moderators review millions of flags every year, resulting in an unmatched diversity of over 83+ million human-verified questions and answers curated across more than 69,000 topics over 17+ years.

How can I access Stack Overflow data?

Customers can gain real-time access to Stack Overflow data via the Stack Exchange API. Curated data samples are also accessible through a web form on this page and popular data marketplaces, such as Snowflake and Databricks Marketplace.

How can I use Stack Overflow data?

In general, companies use question-and-answer data like Stack Overflow’s to train and fine-tune both LLMs and SLMs; improve the accuracy of RAG search; deepen agentic reasoning capabilities; boost the reliability of AI chatbots and copilots, and enrich knowledge graphs and search.

Our knowledge, shared

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