# Characterising Open Source Co-opetition in Company-hosted Open Source Software Projects: The Cases of PyTorch, TensorFlow, and Transformers

arXiv: https://arxiv.org/abs/2410.18241 · HTML: https://mlsanity.com/paper/2410.18241/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 121 references that are in the map.
- First posted on arXiv 23 Oct 2024.

## Builds on (most cited first, 14 of 14)

- [Llama 2: Open Foundation and Fine-Tuned Chat Models](https://mlsanity.com/paper/2307.09288/) (2023)
- [TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems](https://mlsanity.com/paper/1603.04467/) (2016)
- [The AI Community Building the Future? A Quantitative Analysis of Development Activity on Hugging Face Hub](https://mlsanity.com/paper/2405.13058/) (2024)
- [BigScience: A Case Study in the Social Construction of a Multilingual Large Language Model](https://mlsanity.com/paper/2212.04960/) (2022)
- [Public-private funding models in open source software development: A case study on scikit-learn](https://mlsanity.com/paper/2404.06484/) (2024)
- [Systematic Literature Review of Commercial Participation in Open Source Software](https://mlsanity.com/paper/2405.16880/) (2024)
- [Do software firms collaborate or compete? A model of coopetition in community-initiated OSS projects](https://mlsanity.com/paper/1808.06489/) (2018)
- [Why Companies "Democratise" Artificial Intelligence: The Case of Open Source Software Donations](https://mlsanity.com/paper/2409.17876/) (2024)
- [Collaboration in the open-source arena: The WebKit case](https://mlsanity.com/paper/1401.5996/) (2014)
- [Cooperation among competitors in the open-source arena: The case of OpenStack](https://mlsanity.com/paper/1612.09462/) (2016)
- [How Firms Adapt and Interact in Open Source Ecosystems: Analyzing Stakeholder Influence and Collaboration Patterns](https://mlsanity.com/paper/2208.02628/) (2022)
- [Lessons Learned from Applying Social Network Analysis on an Industrial Free/Libre/Open Source Software Ecosystem](https://mlsanity.com/paper/1507.04587/) (2015)
- [Coopetition of software firms in Open source software ecosystems](https://mlsanity.com/paper/1711.07049/) (2017)
- [A method for analyzing stakeholders' influence on an open source software ecosystem's requirements engineering process](https://mlsanity.com/paper/2208.00062/) (2022)

## Built on by (most cited first, 3 of 3)

- [A Cartography of Open Collaboration in Open Source AI: Mapping Practices, Motivations, and Governance in 14 Open Large Language Model Projects](https://mlsanity.com/paper/2509.25397/) (2025)
- [Reckoning with the Political Economy of AI: Avoiding Decoys in Pursuit of Accountability](https://mlsanity.com/paper/2604.16106/) (2026)
- [Large Language Models for Analyzing Enterprise Architecture Debt in Unstructured Documentation](https://mlsanity.com/paper/2604.00046/) (2026)

## Abstract (arXiv)

Companies, including market rivals, have long collaborated on the development of open source software (OSS), resulting in a tangle of co-operation and competition known as "open source co-opetition". While prior work investigates open source co-opetition in OSS projects that are hosted by vendor-neutral foundations, we have a limited understanding thereof in OSS projects that are hosted and governed by one company. Given their prevalence, it is timely to investigate open source co-opetition in such contexts. Towards this end, we conduct a mixed-methods analysis of three company-hosted OSS projects in the artificial intelligence (AI) industry: Meta's PyTorch (prior to its donation to the Linux Foundation), Google's TensorFlow, and Hugging Face's Transformers. We contribute three key findings. First, while the projects exhibit similar code authorship patterns between host and external companies (80%/20% of commits), collaborations are structured differently (e.g., decentralised vs. hub-and-spoke networks). Second, host and external companies engage in strategic, non-strategic, and contractual collaborations, with varying incentives and collaboration practices. Some of the observed collaborations are specific to the AI industry (e.g., hardware-software optimizations or AI model integrations), while others are typical of the broader software industry (e.g., bug fixing or task outsourcing). Third, single-vendor governance creates a power imbalance that influences open source co-opetition practices and possibilities, from the host company's singular decision-making power (e.g., the risk of license change) to their community involvement strategy (e.g., from over-control to over-delegation). We conclude with recommendations for future research.