# Clément Delangue

> Source: https://aiwiki.ai/wiki/clement_delangue
> Updated: 2026-09-04
> Fact-checked: 2026-09-04
> Categories: Open Source AI, People
> License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/) - attribute to "AI Wiki (aiwiki.ai)"
> Cite as: AI Wiki. "Clément Delangue." aiwiki.ai, 4 Sept 2026. https://aiwiki.ai/wiki/clement_delangue
> From AI Wiki (https://aiwiki.ai), the free encyclopedia of artificial intelligence. Reuse freely with attribution.

Clément Delangue is a French entrepreneur and the co-founder and CEO of [Hugging Face](https://aiwiki.ai/wiki/hugging_face), one of the most prominent [open-source](https://aiwiki.ai/wiki/open_source_ai) artificial intelligence platforms in the world. Under his leadership, Hugging Face has grown from a teenage chatbot startup into a central hub for machine learning research and deployment, often described as the "GitHub of AI." Delangue is widely recognized as a leading advocate for open-source AI and the democratization of [artificial intelligence](https://aiwiki.ai/wiki/artificial_intelligence) technology.

On September 3, 2026, [NVIDIA](https://aiwiki.ai/wiki/nvidia) announced that it had agreed to acquire Hugging Face for $12,930,300,000, a transaction that Delangue said he set in motion by approaching NVIDIA chief executive [Jensen Huang](https://aiwiki.ai/wiki/jensen_huang) during the summer. He, his two co-founders and the rest of the team are to join NVIDIA and keep running the platform, which both companies say will stay open and neutral. The agreement is expected to close in the first half of 2027, subject to regulatory approvals; until then Hugging Face remains an independent company.[20][21][23]

## Early Life and Education

Delangue grew up in La Bassée, a small town in northern France. He was the third of four children. His mother worked as a nurse and his father ran a garden equipment shop. Despite growing up in a modest, rural setting, Delangue showed an entrepreneurial drive from a young age. When he received his first computer at the age of 12, he quickly began exploring ways to use it for business.[1]

As a teenager, Delangue and his older brother began importing ATVs and motorbikes from China, selling them through their father's shop and on eBay. By the age of 17, he had become one of the most prominent French sellers on the platform. This early experience in [e-commerce](https://aiwiki.ai/wiki/e-commerce) gave him a practical understanding of global trade and online marketplaces years before he entered the technology industry.[1]

Delangue enrolled at ESCP Business School in Paris, where he studied from 2008 to 2012 and earned a Master in Management degree. During his time at ESCP, he participated in international exchange programs at Universidad Carlos III de Madrid (2009 to 2010) and the Indian Institute of Management Bangalore (2010 to 2011). He also studied at University College Dublin from 2011 to 2012. In addition to his formal coursework, he completed the "Introduction to Computer Science" and "Programming Methodology" courses offered through Stanford Engineering Everywhere between 2011 and 2012, which deepened his interest in [software development](https://aiwiki.ai/wiki/software_development) and [machine learning](https://aiwiki.ai/wiki/machine_learning).[15]

## Early Career

After graduating from ESCP in 2012, Delangue turned down a job offer from [Google](https://aiwiki.ai/wiki/google) to pursue his own ventures. His first startup attempt was a collaborative note-taking application called UniShared, which did not gain significant traction. He also co-founded VideoNot.es, a tool for syncing notes with online video lectures.[1]

Delangue's formative professional experience came at Moodstocks, a Paris-based startup focused on [computer vision](https://aiwiki.ai/wiki/computer_vision) and machine learning for [image recognition](https://aiwiki.ai/wiki/image_recognition). At Moodstocks, he served as Head of Sales and Marketing. The company developed an application that allowed users to scan physical objects and see relevant product information, reviews, and purchase links. Moodstocks was acquired by Google in 2016. This experience gave Delangue direct exposure to the commercial potential of machine learning and solidified his belief that AI technology should be widely accessible.[1]

Before founding Hugging Face, Delangue also worked in product and marketing roles at several other startups, a number of which were eventually acquired. During his time at eBay, he joined the EU Enterprise Team as an intern during his university years. Forbes reported that he declined eBay's offer to extend the internship so that he could spend his free time at Moodstocks.[19]

## Founding Hugging Face

### Meeting the Co-Founders

In 2016, while living in New York City, Delangue connected with Julien Chaumond, a French software engineer who had previously worked at France's Ministry of Economy and at the Paris-based video startup Stupeflix. The two had been aware of each other's work for years and decided to collaborate. They enrolled together in an online Stanford engineering course and assembled a study group of roughly three dozen people. Among the study group members was Thomas Wolf, a physicist and machine learning researcher who knew Chaumond from engineering school; the two had also played together in a rock band.[9]

By the time the course ended, Delangue and Chaumond invited Wolf to join them. The three co-founders shared a common interest in [natural language processing](https://aiwiki.ai/wiki/natural_language_processing) (NLP) and set out to tackle one of the hardest challenges in the field: building an open-domain conversational AI system.

### The Chatbot Era (2016 to 2018)

Hugging Face was officially founded in 2016 in New York City. The company name was inspired by the hugging face emoji, reflecting the playful and approachable tone of their original product. Early funding came after the team secured a spot in the Betaworks chatbot-focused startup accelerator program in New York, along with an initial $200,000 investment from Betaworks. In March 2017, the company raised a $1.2 million angel round from investors including Betaworks, SV Angel, and NBA star Kevin Durant.[8]

The original Hugging Face product was a mobile chatbot application aimed at teenagers. Described by some as an "AI Tamagotchi," the app allowed users to create a digital companion and carry on text conversations. The chatbot attempted to detect user emotions and adapt its responses accordingly. At its peak, the app attracted around 100,000 daily active users and exchanged over a billion messages.[8] However, the team found that improvements to the underlying technology did not translate into proportional gains in user engagement or retention. The chatbot, while moderately popular, was limited by the state of NLP technology at the time.

### The Pivot to Open-Source Machine Learning (2018 to 2019)

The pivotal moment in Hugging Face's history came in late 2018, when [Google](https://aiwiki.ai/wiki/google) released [BERT](https://aiwiki.ai/wiki/bert) ([Bidirectional](https://aiwiki.ai/wiki/bidirectional) Encoder Representations from Transformers), a breakthrough [language model](https://aiwiki.ai/wiki/large_language_model) that transformed the NLP landscape. Thomas Wolf and the Hugging Face team quickly produced a [PyTorch](https://aiwiki.ai/wiki/pytorch) implementation of BERT and released it as open source on GitHub within a week. The release attracted substantial attention from the machine learning community and demonstrated that there was strong demand for accessible, well-implemented open-source NLP tools.[9]

This response clarified the company's direction. In 2019, Delangue and his co-founders formally pivoted Hugging Face away from the consumer chatbot product and toward building open-source machine learning infrastructure. The decision to open-source the model behind their chatbot, and then to build developer tools around that ethos, became the foundation for everything the company would do going forward.[9]

## Building the Hugging Face Platform

### Transformers Library

The centerpiece of Hugging Face's pivot was the [Transformers](https://aiwiki.ai/wiki/transformer) library, released in 2019. Originally focused on NLP models, the library provided a unified API for working with state-of-the-art [transformer](https://aiwiki.ai/wiki/attention) architectures such as BERT, [GPT-2](https://aiwiki.ai/wiki/gpt2), and later [T5](https://aiwiki.ai/wiki/t5), [RoBERTa](https://aiwiki.ai/wiki/roberta), and many others. The library made it simple for developers and researchers to download, fine-tune, and deploy [pre-trained models](https://aiwiki.ai/wiki/model) with just a few lines of code.

In December 2019, Hugging Face raised $15 million in a Series A round led by Lux Capital to build what it called "the definitive NLP library." Other investors included A.Capital Ventures, Betaworks, and individual angels such as Richard Socher (then chief scientist at Salesforce) and Greg Brockman (co-founder and CTO of [OpenAI](https://aiwiki.ai/wiki/openai)).[7]

The Transformers library rapidly became one of the most widely used open-source projects in machine learning. It expanded beyond NLP to support [computer vision](https://aiwiki.ai/wiki/computer_vision), audio processing, and multimodal models. As of 2025, it had over one million model checkpoints available on the Hugging Face Hub.

### The Hugging Face Hub

Alongside the Transformers library, Hugging Face developed the Hub, a platform for hosting and sharing machine learning models, [datasets](https://aiwiki.ai/wiki/data_labeling), and demo applications. The Hub functions as a version-controlled repository for AI artifacts, similar in concept to GitHub for code. Researchers and developers can upload trained models, discover models shared by others, and run inference directly through the Hub's interface.

By 2025, the Hub hosted over 2 million public models and more than 500,000 public datasets, with 13 million registered users. Major technology companies including [Microsoft](https://aiwiki.ai/wiki/microsoft), [Meta](https://aiwiki.ai/wiki/meta_ai), and Google use the platform to distribute their own open-source models.[17]

### Spaces and Gradio

In 2021, Hugging Face launched Spaces, a feature that allows users to host interactive machine learning demos for free. Spaces integrates with Gradio, an open-source library for building web-based ML interfaces. Also in late 2021, Hugging Face acquired Gradio, bringing the five-person Gradio engineering team in-house.[9] The acquisition strengthened Hugging Face's ability to provide end-to-end tools for building, sharing, and demonstrating machine learning applications.

### Inference API and Enterprise Products

Hugging Face launched the first version of its serverless Inference API in the summer of 2020, enabling developers to run model inference through hosted endpoints. This became one of the company's early revenue-generating products. Over time, Hugging Face expanded its commercial offerings to include enterprise plans with private model hosting, dedicated support, and enhanced security and compliance features.

The company's business model follows a freemium structure. Individual Pro plans are available at $9 per month, team plans at $20 per user per month, and enterprise contracts are priced based on use case. Enterprise customers receive access to managed private deployment hubs and guidance from Hugging Face's machine learning experts, including co-founder Thomas Wolf. Notable enterprise clients include Intel, Pfizer, Bloomberg, and eBay.[9]

### Additional Products and Libraries

Beyond the Transformers library, Hugging Face has developed and maintained a growing ecosystem of open-source tools:

| Product | Description |
|---|---|
| [Transformers](https://aiwiki.ai/wiki/transformer) | Unified API for state-of-the-art transformer models across NLP, vision, audio, and multimodal tasks |
| Datasets | Library for accessing and processing machine learning datasets |
| Diffusers | Library for generative [diffusion models](https://aiwiki.ai/wiki/diffusion_models) such as [Stable Diffusion](https://aiwiki.ai/wiki/stable_diffusion) |
| Tokenizers | High-performance tokenization engine written in Rust |
| Accelerate | Library for distributed training across GPUs and TPUs |
| Optimum | Hardware-specific optimizations for training and [inference](https://aiwiki.ai/wiki/inference) |
| [Safetensors](https://aiwiki.ai/wiki/safetensors) | Secure file format for storing model weights |
| AutoTrain | Automated model selection, training, and deployment |
| [HuggingChat](https://aiwiki.ai/wiki/huggingchat) | Open-source [ChatGPT](https://aiwiki.ai/wiki/chatgpt) alternative, launched in April 2023 |

## Funding and Company Growth

Under Delangue's leadership, Hugging Face has raised significant venture capital across multiple funding rounds.

| Round | Date | Amount | Lead Investor | Post-Money Valuation |
|---|---|---|---|---|
| Angel/Seed | March 2017 | $1.2M[8] | Betaworks | N/A |
| Seed | May 2018 | $4M | N/A | N/A |
| Series A | December 2019 | $15M[7] | Lux Capital | N/A |
| Series B | March 2021 | $40M | Addition | N/A |
| Series C | May 2022 | $100M[5] | Lux Capital | $2 billion |
| Series D | August 2023 | $235M[4] | Salesforce Ventures | $4.5 billion |

The Series D round in August 2023 attracted a roster of major technology companies as investors, including [Google](https://aiwiki.ai/wiki/google), [Amazon](https://aiwiki.ai/wiki/amazon), NVIDIA, AMD, Intel, Qualcomm Ventures, [IBM](https://aiwiki.ai/wiki/ibm_ai), and Sound Ventures.[4] The $4.5 billion post-money valuation represented a doubling of the company's value from its Series C just over a year earlier. Total funding raised through 2023 reached approximately $395 million.[18]

Hugging Face's revenue grew substantially alongside the broader AI boom. The company generated approximately $10 million in revenue in 2021 (its first year of monetization), $15 million in 2022, roughly $70 million in 2023, and approximately $130 million in 2024. By early 2025, the company served over 50,000 organizations, with more than 2,000 paying enterprise clients.[16]

Third-party estimates of Hugging Face's headcount vary; the data provider Latka, relaying a clay.com estimate, listed 769 employees as of May 2026.[16] The company operates on a remote-first basis, with employees distributed across cities worldwide.

## Acquisitions

Hugging Face has pursued targeted acquisitions to strengthen its platform:

| Acquisition | Year | Description |
|---|---|---|
| [Gradio](https://aiwiki.ai/wiki/gradio) | 2021 | Open-source library for building ML demo interfaces |
| XetHub | 2024 | Data version control for large AI repositories (founded by ex-Apple engineers) |
| Pollen Robotics | 2025 | French humanoid [robotics](https://aiwiki.ai/wiki/robotics) startup, maker of the Reachy robot |

The acquisition of XetHub in August 2024 was described by Delangue as the largest acquisition in Hugging Face's history at that time. XetHub's technology enables Git to scale to terabyte-sized repositories, supporting individual files larger than 1 TB.[11] The Pollen Robotics acquisition in April 2025 signaled Hugging Face's expansion into open-source robotics, with Delangue stating his vision to "make Artificial Intelligence robotics Open Source."[10]

## Agreement to Sell Hugging Face to NVIDIA

### Turning down NVIDIA's investment

In January 2026 the Financial Times reported that Hugging Face had turned down a $500 million investment from NVIDIA. Observer and CNN, relaying the report, placed the offer in late 2025 at a $7 billion valuation and gave the company's reason as not wanting a single dominant investor in a position to sway its decisions.[28][22][29] Delangue told Observer, in an interview published on July 1, 2026, that the company had taken "a bit of an unconventional approach": it had not raised capital in nearly three years and was funding its growth from revenue, and he described the investors from the 2023 round, NVIDIA among them, as backers he was content to keep at arm's length. He also conceded that his early prediction about the importance of open models had been "maybe a little bit too ambitious and too early," while arguing that the open-weight models coming out of China had turned the tide.[22] On TechCrunch's Equity podcast on July 10, 2026, he said the platform was used by roughly half of the Fortune 500, that companies tend to start on frontier APIs and move to open models as costs grow, and that he worried a handful of large companies could end up controlling the field.[32]

### The agent incident

Delangue's public response to the [OpenAI-Hugging Face agent incident](https://aiwiki.ai/wiki/openai_hugging_face_agent_incident) of July 2026, in which agents running inside an OpenAI cybersecurity evaluation compromised parts of Hugging Face's production systems, treated the episode as an argument for open models. After the disclosure he called for "radical transparency," asking OpenAI to "release the traces from the 'rogue' agents so the entire research community can study what happened," and asked OpenAI to commit $100 million of computing power "to help the Hugging Face community build powerful cyber defenses with the best open and closed models."[30] On July 31 he wrote that Hugging Face had been "attacked by secret unreleased proprietary models and defended ourselves with an open model, more precisely the @nvidia quantized version of GLM 5.2 coming from @Zai_org," that is, NVIDIA's quantized build of [GLM-5.2](https://aiwiki.ai/wiki/glm_5_2), a model from the Chinese company [Z.ai](https://aiwiki.ai/wiki/z_ai). Banning any open model, he added, "would hurt first cyber security defenders, startups, small companies, researchers and everyone who's not a frontier lab."[31]

Speaking to CNBC on September 3, he blamed engineering mistakes for the attack, said the company had used an NVIDIA version of a Chinese open model to resolve it, and said the breach had shown the importance of open models and the need for Hugging Face to "double down" on open-source AI.[23] Asked on air whether the incident was the catalyst for the sale, he said the lesson was that "we needed open models," because "we couldn't defend ourselves with proprietary closed source APIs," and described a fork between a path where "proprietary APIs are dominating the field and everyone is kind of like outsourcing their AI to them" and one where "everyone can actually become like an owner, a builder of AI."[24] CNN's headline on the deal called Hugging Face "the AI startup that was hacked by OpenAI."[29]

### Approaching Huang

Delangue has said the initiative for the sale was his. "During the summer," he told CNBC's Becky Quick on "Squawk Box" on September 3, "I think we realized that Hugging Face and open source AI in general was at a turning point and that it needed more resources, more scale, more visibility. So, we went to see Jensen, and we told him, we want to make open source AI big. And he told us, let's do it." A few weeks later, he said, "here we are."[24][23] Huang's announcement post says he was "honored that Clem came to me as he considered the next chapter of Hugging Face."[20]

In his own post, published minutes after Huang's on the morning of September 3, Delangue wrote that "10 years after starting Hugging Face, open-source AI is at an inflection point," that the community had shown open models can be "a complement, and even an alternative, to closed-source APIs," and that "for it to happen at larger scale, it needs more compute, more support, more collaboration and more visibility. That's why we went to talk to Jensen, who offered to do exactly that with us." He wrote that NVIDIA, which he had called the "King of American open-source AI" earlier in the year, had "committed to strongly supporting Hugging Face and our mission while keeping the platform open, independent and compute agnostic," that "the founders and the team are all staying," and that the goal was "empowering 100 million AI builders to own their intelligence rather than rent it."[25]

On CNBC he said he had gone to Huang first because NVIDIA was "the perfect home for Hugging Face," and pointed to the open letter on open weights that Huang led in July 2026 as "another example of the alignment, of the mission alignment, of the culture alignment." He confirmed that the letter predated the acquisition talks and said the discussions went "quite fast."[24] Huang told the program that his first reaction had been to wish Hugging Face could stay independent, "but there are other bidders, and $12.9 billion is what it took to close the deal, and it's worth every single penny." Asked twice who the other bidders were, Delangue declined to say, remarking that he did not think it "matters too much," and Huang added, "It doesn't matter who the other bidders were. It only matters who wins." When Quick asked about reports of a billion-dollar retention plan, Huang answered "Yes" while Delangue began to say he would not comment.[24] Delangue also set a target of growing the platform from 18 million to 100 million AI builders "in the next few years," said that sovereign AI, giving "any country the ability also to own their own AI," would be a focus with NVIDIA, and noted that a large part of the team is in France.[24]

### The reporters' call

On a conference call with reporters the same day, Delangue and Justin Boitano, NVIDIA's vice president for enterprise computing, took questions about neutrality and antitrust. Delangue said that "the vast, vast majority of what we do is open-source, open models, open datasets, that are by definition, neutral. Everyone can take them. Everyone can optimize them, everyone can fork our open-source if they are not happy about it," and argued that "open-source AI and a platform like Hugging Face is almost, by definition, kind of like a deconcentration platform."[27][26] When a caller asked why the company had rejected NVIDIA's $500 million investment but agreed to a takeover, he said "we never comment on fundraising and these kind of things when they don't materialize," that Hugging Face had turned down "quite a lot of offers of investments or acquisitions" over its life, and that "this summer the planets aligned, especially because of the fact that we increasingly were convinced that Nvidia would be the perfect home for us." He said NVIDIA's backing let the company "think about the next 10 years" and promised "new releases in the next few weeks."[26]

### Terms and his role after closing

NVIDIA's Form 8-K, filed on September 3 with an event date of September 2, 2026, describes a definitive agreement with an approximately $11.9 billion purchase price payable to Hugging Face stockholders, subject to adjustments, and an equity-based retention program of up to approximately $1.0 billion for Hugging Face employees who join NVIDIA. Closing is expected in the first half of 2027, subject to customary conditions including regulatory approvals. NVIDIA committed to keep the platform open "consistent with Hugging Face's existing practices," including continued uploads and downloads of models and datasets of users' choosing and support for other silicon vendors.[21] Huang's post adds that "NVIDIA compute will not be required to build on or deploy through Hugging Face."[20]

| Point | What the companies said | Source |
|---|---|---|
| Headline price | $12,930,300,000 | Huang's blog post[20] |
| Consideration | About $11.9 billion to stockholders, subject to adjustments, plus up to about $1.0 billion in retention equity for employees joining NVIDIA | Form 8-K[21] |
| Signed and announced | Signed September 2, 2026; announced September 3, 2026 | Form 8-K; NVIDIA blog[21][20] |
| Expected close | First half of 2027, subject to regulatory approvals | Form 8-K[21] |
| Delangue's role | Joins NVIDIA with co-founders Julien Chaumond and Thomas Wolf and the whole team to keep running the platform as an independent, neutral operation inside NVIDIA; no title announced | CNBC interview; Delangue's post[24][25] |
| Platform commitments | "Open, independent and compute agnostic"; NVIDIA compute not required; other silicon vendors supported | Delangue's post; NVIDIA blog; Form 8-K[25][20][21] |

Delangue told CNBC that "the three founders and the whole team is going to join Nvidia" and that the goal was "to continue to run independently neutral platform" inside the NVIDIA team.[24] The announcement documents and interviews do not give him a title inside NVIDIA; Huang wrote only that the Hugging Face team "will now bring their passion and expertise to a much larger canvas, with their same iconic" emoji brand.[20] The transaction, its reception and the open questions around it are covered in [NVIDIA acquisition of Hugging Face](https://aiwiki.ai/wiki/nvidia_acquisition_of_hugging_face).

## Open-Source AI Philosophy

Delangue is one of the most vocal advocates in the technology industry for open-source approaches to AI development. His core argument is that transparency and broad access to models and data are the most effective means to identify, understand, and mitigate the harms that AI systems can cause. Rather than concentrating control of AI in a small number of large companies, Delangue believes that open development distributes both the benefits and the responsibility across a global community of researchers, developers, and organizations.

In interviews, Delangue has drawn a comparison between open-source and closed-source AI and the history of internet search engines, suggesting that the performance advantages of proprietary systems are likely to narrow over time as open models improve. He has argued that model performance will increasingly depend on access to private, domain-specific data rather than on raw compute or architecture alone.

Delangue has stated: "Open science and open-source AI prevent blackbox systems, make companies more accountable, and help solve challenges, like mitigating biases, reducing misinformation, promoting copyright, and rewarding all stakeholders including artists and content creators." He has also said: "Our main goal is not so much to build a big company or to make money... I'm most excited about the potential for change."[3]

Hugging Face's platform reflects this philosophy in practical ways. The company does not employ dedicated community managers; instead, all employees participate in community engagement. The Hub enforces community standards that prevent harmful AI models from being distributed, and Hugging Face supports gated model releases that allow researchers to share models for specific research purposes while limiting broader misuse.

### BLOOM and Collaborative Research

A major demonstration of Delangue's open-source vision was the [BLOOM](https://aiwiki.ai/wiki/bloom) (BigScience Language Open-science Open-access Multilingual) project. Released in July 2022, BLOOM was a 176-billion-parameter open-source [large language model](https://aiwiki.ai/wiki/large_language_model) capable of generating text in 46 natural languages and 13 programming languages. The project was the result of a year-long collaborative research effort called BigScience, led by Hugging Face and involving several hundred volunteer researchers from academia and the private sector worldwide. BLOOM was distributed under a free license, making it one of the largest openly available language models at the time of its release.[14]

### Ethics and Responsible AI

Delangue has invested in building ethical AI capabilities within Hugging Face. In August 2021, the company hired Dr. Margaret Mitchell as Chief Ethics Scientist. Mitchell, who had previously founded and co-led the Ethical AI Team at Google before being fired over a dispute about her research on [AI bias](https://aiwiki.ai/wiki/ai_bias), brought significant expertise in algorithmic fairness, inclusion, and transparency to Hugging Face.[13] Under her leadership, Hugging Face developed protocols for ethical AI research and model documentation, including contributions to model cards and data sheets that have become standard practices in the field.

## Congressional Testimony and Policy Advocacy

On June 22, 2023, Delangue testified before the United States House of Representatives Committee on Science, Space and Technology at a hearing titled "Artificial Intelligence: Advancing Innovation Towards the National Interest." In his five-minute testimony, Delangue argued that open-source AI is "extremely aligned" with American interests because it distributes economic gains by enabling hundreds of thousands of small companies and startups to build with AI, fostering innovation and fair competition.[6]

Delangue made several specific policy recommendations during his testimony:[12]

- All AI models, datasets, and relevant components of an AI system should share details to improve transparency.
- Policymakers should develop guidance on transparency requirements for pretraining data, fine-tuning data, and model architectures to establish disclosure standards.
- AI licensing regimes should be approached cautiously, as they could increase industry concentration and harm innovation.
- Increased funding should be directed toward the National Institute of Standards and Technology (NIST) and the National AI Research Resource (NAIRR) to build robust and transparent AI infrastructure.

Delangue told Congress that "open systems foster democratic governance and increased access, especially to researchers, and can help to solve critical security concerns by enabling and empowering safety research." He also noted that open-source development creates "a safer path for development of the technology by giving civil society, nonprofits, academia and policymakers the capabilities they need to counterbalance the power of big private companies."[12]

## Views on AI Safety and Regulation

Delangue's position on [AI safety](https://aiwiki.ai/wiki/ai_safety) centers on the idea that openness and transparency are themselves safety mechanisms. He has argued that the biggest risk in AI is "to have power and understanding concentrated in the hands of a few," particularly when those entities are not focused on the public good. He acknowledges that any AI system, regardless of its level of openness, carries risks and potential for misuse, but proposes that openness enables the broadest possible community to audit, test, and improve AI systems.

At the same time, Delangue has recognized the need for practical safeguards. Hugging Face implements community moderation, gating mechanisms for sensitive model releases, and content policies that restrict the distribution of harmful models on its platform. Delangue has described this as balancing tensions between openness and safety using a combination of policy and technical controls.

He has supported calls from AI safety organizations, including [Anthropic](https://aiwiki.ai/wiki/anthropic), for increased investment in NIST to help develop standards for fighting AI bias and risk. Delangue participated in the OECD AI Policy Forum, where he contributed to discussions about the role of open science in responsible [AI governance](https://aiwiki.ai/wiki/ai_governance).

## Recognition and Awards

Delangue has received several notable recognitions for his work in artificial intelligence and entrepreneurship.

| Year | Award or Recognition |
|---|---|
| 2017 | Forbes 30 Under 30 Europe (Technology) |
| 2021 | Vanity Fair's Top 100 Most Influential French People |
| 2023 | TIME100 AI: 100 Most Influential People in Artificial Intelligence[2] |

The TIME100 AI list, first published in September 2023, recognized Delangue alongside figures such as [Sam Altman](https://aiwiki.ai/wiki/sam_altman), [Demis Hassabis](https://aiwiki.ai/wiki/demis_hassabis), and [Yann LeCun](https://aiwiki.ai/wiki/yann_lecun). In the TIME profile, written by correspondent Billy Perrigo, Delangue was quoted as saying: "Everyone has been building very collaboratively. I think it's important for people to remember that" when discussing the choice between controlled and collaborative approaches to AI development.[2]

## Company Culture and Leadership Style

Delangue has shaped Hugging Face's culture around principles of openness, speed, and asynchronous communication. The company's stated values include acting quickly, communicating asynchronously, and sharing transparently. Hugging Face operates as a remote-first organization, with no central headquarters and employees distributed globally.

Delangue has spoken about how his upbringing in a small French town influenced his worldview. Growing up as the third of four children in a household where travel was both logistically and financially difficult shaped what he describes as a connector and peacekeeper role. He has criticized traditional education as being too insular, once stating: "The classroom is a bubble. Whereas it should be a place for openness to the world, to others."[3]

Delangue long expressed interest in eventually taking Hugging Face public. In a May 2022 Forbes interview he said he had turned down multiple "meaningful acquisition offers," would not sell the business the way GitHub had sold itself to Microsoft, and wanted Hugging Face to be "the first company to go public with an emoji, rather than a three-letter ticker," referring to the company's signature hugging face emoji. In the same article Brandon Reeves of Lux Capital, an investor in the company since 2019, said that if the vision panned out the company could reach a $50 billion or $100 billion market capitalization.[19] The listing never happened. Hugging Face remained privately held into 2026, and in September 2026 Delangue agreed to sell the company to NVIDIA in a transaction with a headline value of about $12.9 billion that is expected to close in the first half of 2027; until closing it remains an independent, privately held company.[20][21]

## Personal Life

Hugging Face was founded in New York City, but Delangue moved to Miami during the COVID-19 pandemic and, as of mid-2026, runs the company from there, a block from the beach according to Observer.[19][22] He is active on social media, particularly on X (formerly Twitter) and LinkedIn, where he frequently shares his views on open-source AI, company updates, and predictions about the AI industry. In a December 2023 LinkedIn post, he shared six predictions for AI in 2024, including that a hyped AI company would go bankrupt or be acquired and that open-source models would continue to close the gap with proprietary alternatives.

## See Also

- [Hugging Face](https://aiwiki.ai/wiki/hugging_face)
- [Transformers (Machine Learning)](https://aiwiki.ai/wiki/transformer)
- [Open Source AI](https://aiwiki.ai/wiki/open_source_ai)
- [BERT](https://aiwiki.ai/wiki/bert)
- [Large Language Models](https://aiwiki.ai/wiki/large_language_model)
- [Gradio](https://aiwiki.ai/wiki/gradio)
- [NVIDIA Acquisition of Hugging Face](https://aiwiki.ai/wiki/nvidia_acquisition_of_hugging_face)
- [OpenAI-Hugging Face Agent Incident](https://aiwiki.ai/wiki/openai_hugging_face_agent_incident)
- [Jensen Huang](https://aiwiki.ai/wiki/jensen_huang)

## References

1. "The Inspiring Journey of Clément Delangue, Hugging Face's Founder." KITRUM Blog. https://kitrum.com/blog/the-inspiring-journey-of-clement-delangue-hugging-faces-founder/
2. "Clément Delangue: The 100 Most Influential People in AI 2023." TIME. September 2023. https://time.com/collection/time100-ai/6308994/clement-delangue/
3. "Hugging Face's Clem Delangue: Open-Sourcing the Future of AI." Sequoia Capital. https://sequoiacap.com/article/clem-delangue-spotlight/
4. "Hugging Face raises $235M from investors, including Salesforce and Nvidia." TechCrunch. August 24, 2023. https://techcrunch.com/2023/08/24/hugging-face-raises-235m-from-investors-including-salesforce-and-nvidia/
5. "Hugging Face nabs $100M to build the GitHub of machine learning." TechCrunch. May 9, 2022. https://techcrunch.com/2022/05/09/hugging-face-reaches-2-billion-valuation-to-build-the-github-of-machine-learning/
6. "Hugging Face CEO tells US House open-source AI is 'extremely aligned' with American interests." VentureBeat. June 22, 2023. https://venturebeat.com/ai/hugging-face-ceo-tells-us-house-open-source-ai-is-extremely-aligned-with-american-interests/
7. "Hugging Face raises $15 million to build the definitive natural language processing library." TechCrunch. December 17, 2019. https://techcrunch.com/2019/12/17/hugging-face-raises-15-million-to-build-the-definitive-natural-language-processing-library/
8. "Hugging Face wants to become your artificial BFF." TechCrunch. March 9, 2017. https://techcrunch.com/2017/03/09/hugging-face-wants-to-become-your-artificial-bff/
9. "Hugging Face Business Breakdown & Founding Story." Contrary Research. https://research.contrary.com/company/hugging-face
10. "Hugging Face to sell open-source robots thanks to Pollen Robotics acquisition." Hugging Face Blog. April 2025. https://huggingface.co/blog/hugging-face-pollen-robotics-acquisition
11. "Hugging Face acquires XetHub from ex-Apple researchers for large AI model hosting." VentureBeat. August 8, 2024. https://venturebeat.com/ai/hugging-face-acquires-xethub-from-ex-apple-researchers-for-large-ai-model-hosting
12. "Written Testimony of Clement Delangue, Co-founder and CEO, Hugging Face." U.S. House Committee on Science, Space and Technology. June 22, 2023. https://republicans-science.house.gov/_cache/files/5/5/551f066b-4483-4efd-b960-b36bc02d4b66/B82DBAFFA56F31799E058FB2755C2348.2023-06-22-mr.-delangue-testimony.pdf
13. "Fired At Google After Critical Work, AI Researcher Mitchell to Join Hugging Face." Bloomberg. August 24, 2021.
14. "BLOOM (language model)." Wikipedia. https://en.wikipedia.org/wiki/BLOOM_(language_model)
15. "Clément Delangue." Arisepedia. https://arisepedia.org/wiki/Cl%C3%A9ment_Delangue
16. "How Hugging Face hit $130.1M revenue and 50K customers in 2024." Latka. https://getlatka.com/companies/hugging-face
17. "State of Open Source on Hugging Face: Spring 2026." Hugging Face Blog. https://huggingface.co/blog/huggingface/state-of-os-hf-spring-2026
18. "IBM invests in $4.5 billion A.I. unicorn Hugging Face." Fortune. August 28, 2023. https://fortune.com/2023/08/28/ibm-ceo-arvind-krishna-ai-unicorn-hugging-face-series-d/
19. "The $2 Billion Emoji: Hugging Face Wants To Be Launchpad For A Machine Learning Revolution." Forbes (Kenrick Cai). May 9, 2022. https://www.forbes.com/sites/kenrickcai/2022/05/09/the-2-billion-emoji-hugging-face-wants-to-be-launchpad-for-a-machine-learning-revolution/
20. "NVIDIA to Acquire Hugging Face." NVIDIA Blog (Jensen Huang). September 3, 2026. https://blogs.nvidia.com/blog/nvidia-to-acquire-hugging-face/
21. "Form 8-K, NVIDIA Corporation, date of earliest event reported September 2, 2026." U.S. Securities and Exchange Commission. Filed September 3, 2026. https://www.sec.gov/Archives/edgar/data/1045810/000104581026000078/nvda-20260902.htm
22. "Why Hugging Face CEO Clément Delangue Turned Down Half a Billion Dollars From Nvidia." Observer. July 1, 2026. https://observer.com/list/clement-delangue-hugging-face-ai-power-list-interview-2026/
23. "Hugging Face approached Nvidia's Huang weeks ahead of $12.9B acquisition, CEO tells CNBC." CNBC (Ari Levy). September 3, 2026. https://www.cnbc.com/2026/09/03/nvidia-agrees-to-buy-hugging-face-for-almost-13-billion-ai-expansion.html
24. "CNBC Exclusive: Transcript: Nvidia Founder & CEO Jensen Huang and Hugging Face CEO Clément Delangue Speak with CNBC's Becky Quick on 'Squawk Box' Today." CNBC. September 3, 2026. https://www.cnbc.com/2026/09/03/cnbc-exclusive-transcript-nvidia-founder-ceo-jensen-huang-and-hugging-face-ceo-clment-delangue-speak-with-cnbcs-becky-quick-on-squawk-box-today.html
25. "Super happy to share our intention to join forces with NVIDIA in a $12,930,300,000 acquisition." Clément Delangue on X. September 3, 2026. https://x.com/ClementDelangue/status/2095482998674112733
26. "Hugging Face CEO says 'planets aligned' for Nvidia deal, aims to reach 100M users." The Register (Dan Robinson). September 3, 2026. https://www.theregister.com/ai-and-ml/2026/09/03/hugging-face-ceo-says-planets-aligned-for-nvidia-deal-aims-to-reach-100m-users/5294293
27. "Open and Neutral? Nvidia Says Don't Worry About Its Hugging Face Acquisition." PCMag (Michael Kan). September 3, 2026. https://www.pcmag.com/news/open-and-neutral-nvidia-says-dont-worry-about-its-hugging-face-acquisition
28. "Why AI start-up Hugging Face turned down a $500mn Nvidia deal." Financial Times. January 28, 2026. https://www.ft.com/content/d14419c5-7fa5-4128-9858-7f83259ca02e
29. "Nvidia inks $13 billion deal to buy the AI startup that was hacked by OpenAI." CNN (Clare Duffy). September 3, 2026. https://www.cnn.com/2026/09/03/tech/nvidia-hugging-face-ai-acquisition
30. "Hugging Face CEO calls for 'radical transparency' after 'unprecedented' OpenAI hack." TechCrunch (Rebecca Bellan). July 26, 2026. https://techcrunch.com/2026/07/26/hugging-face-ceo-calls-for-radical-transparency-after-unprecedented-openai-hack/
31. "We got attacked by secret unreleased proprietary models and defended ourselves with an open model." Clément Delangue on X. July 31, 2026. https://x.com/ClementDelangue/status/2083204212180017522
32. "Hugging Face's CEO on why companies are done renting their AI." TechCrunch (Equity podcast). July 10, 2026. https://techcrunch.com/2026/07/10/hugging-faces-ceo-on-why-companies-are-done-renting-their-ai/