HUGGING FACE: the platform every AI giant has a reason to buy. But at what cost?

In 2023, HUGGING FACE brought SALESFORCE, GOOGLE, AMAZON, NVIDIA, INTEL, AMD, QUALCOMM and IBM onto its cap table. Three years later, that list almost reads like a roll call of potential acquirers. According to The Information, NVIDIA is reportedly prepared to pay $12.9 billion to take control of the platform, nearly 86 times its annualised revenue. The price looks considerable, but each of these groups could turn HUGGING FACE into a distribution channel for its chips, cloud infrastructure or software. Yet the more an acquirer tries to use the platform to favour its own products, the greater the risk of destroying the very neutrality that gives it value.

A funding round that had already mapped the market

Viewed from an industry perspective, the 2023 funding round was less a coalition of investors than a snapshot of the artificial intelligence value chain.

NVIDIA, AMD, INTEL and QUALCOMM manufacture the processors on which models are trained or run. AMAZON and GOOGLE sell the cloud infrastructure needed for those operations. IBM and SALESFORCE want to integrate models into large companies’ systems. Each had a different reason to back HUGGING FACE, but they all had one thing in common: the platform made it easier for developers to access the technologies they wanted to sell them.

HUGGING FACE thus positioned itself at the intersection of these interests without having to choose a side. By the summer of 2026, the company hosted nearly 3 million public models, more than one million datasets and 1.44 million Spaces applications. It had 13 million users at the end of 2025 and said that more than 30% of Fortune 500 companies had a verified account.

This position on the board partly explains the $12.9 billion figure attached to its acquisition. Set against the roughly $150 million in annualised revenue attributed to the company, the price represents around 86 times revenue. Such a multiple clearly does not merely pay for subscription software. It puts a price on a network, technical standards and, above all, a position in the developer journey.

The moment when choosing a model becomes a bill

HUGGING FACE is often described as the GITHUB of artificial intelligence. The comparison remains useful, but it no longer captures the platform in full. While GITHUB is primarily used to store, version and distribute code, HUGGING FACE allows users to search for a model, read its documentation, identify the datasets used, download its weights, test a demo, create an adaptation and then run inference through a computing provider.

The journey is now almost seamless: discover → compare → download → adapt → deploy → consume compute.

The final step is the most important economically. Once a developer has selected a model, it must be trained, fine-tuned or run, and those operations generate spending on GPUs, storage, networking and cloud infrastructure.

HUGGING FACE therefore sits at the precise point where a technical decision can turn into an IT bill. The company may not own the data centre that ultimately collects that spending, but it can influence where the money goes. This is why infrastructure sellers have more reason to acquire it than model producers.

NVIDIA wants to funnel models towards its GPUs

NVIDIA’s logic is the most direct. The group has gradually extended its position far beyond the chip. CUDA has established its software environment as a standard among developers. The acquisition of MELLANOX brought it the interconnection technologies required for large clusters. RUN:AI allows it to orchestrate computing resources. NEMO and NIM add the tools needed to build, optimise and deploy models. Finally, DGX CLOUD brings NVIDIA closer to being a fully fledged computing services provider.

HUGGING FACE would provide the missing layer: the developers’ point of entry.

The two companies already work together. Models optimised for NVIDIA can be run as NIM microservices from HUGGING FACE, while the platform is integrated with DGX CLOUD LEPTON. An acquisition would turn this technical proximity into a commercial loop: model discovered on HUGGING FACE → NVIDIA-optimised version → deployment with NIM → execution on NVIDIA GPUs.

The appeal is even greater because the major AI laboratories are trying to reduce their dependence on the chipmaker. GOOGLE has its TPUs, while AMAZON is developing TRAINIUM and INFERENTIA. MICROSOFT has its own accelerators, and OPENAI and ANTHROPIC are also seeking to diversify their infrastructure.

Faced with customers capable of designing their own chips, NVIDIA has an interest in aggregating another source of demand: the thousands of companies, laboratories and developers using open models without owning infrastructure of their own. HUGGING FACE would allow it to turn a fragmented ecosystem into a distribution channel.

MICROSOFT could extend GITHUB all the way to the model

MICROSOFT probably has the strongest product rationale. Through GITHUB, the company already controls the environment in which much of the world’s software is stored and developed. With VISUAL STUDIO and VS CODE, it provides the programming tools. With AZURE, it sells the infrastructure. With MICROSOFT FOUNDRY and COPILOT, it builds the products that use the models.

HUGGING FACE would fill the gap between code and cloud: code on GITHUB → model on HUGGING FACE → development in VS CODE → deployment on AZURE → use in COPILOT or MICROSOFT FOUNDRY.

The two platforms are already closely connected. More than 11,000 models from HUGGING FACE can be deployed in MICROSOFT FOUNDRY and AZURE MACHINE LEARNING. MICROSOFT also has experience that no other potential acquirer can quite match. Since acquiring GITHUB for $7.5 billion in 2018, the group has preserved its brand and interfaces, as well as developers’ ability to deploy their code somewhere other than AZURE. It could try to replicate this model with HUGGING FACE: buy the infrastructure without immediately turning it into a section of the Microsoft store.

The difficulty would be regulatory. A single company would control the leading code repository, one of the leading model repositories, a development environment, a global cloud platform and several AI interfaces used by businesses. The continuity of the journey would be remarkable. So would the concentration.

AMAZON’s main interest is preventing anyone else from buying it

For AMAZON, HUGGING FACE is as much a defensive asset as it is an opportunity. The platform is already integrated with SAGEMAKER, BEDROCK, EC2, ECS and EKS. The two companies are also working to make it easier to use models with TRAINIUM and INFERENTIA, the accelerators AWS developed to reduce its dependence on NVIDIA GPUs.

Acquiring HUGGING FACE would allow AMAZON to steer model training and inference more naturally towards its cloud. More importantly, however, the deal would prevent a competitor from doing the same.

If NVIDIA takes control of the Hub, AWS risks seeing a growing share of models optimised first for CUDA and NIM. If MICROSOFT acquires it, AZURE will gain another advantage among developers. If GOOGLE prevails, TPUs will secure a far more powerful distribution channel.

AMAZON therefore has an interest as a potential owner, but also as a player willing to pay to keep the crossroads out of its neighbour’s garden.

GOOGLE could bring the Hub closer to TPUs, at the risk of duplication

GOOGLE also has strong synergies with HUGGING FACE. The group has its own GEMINI and GEMMA models, TPU accelerators, GOOGLE CLOUD, VERTEX AI and KAGGLE. Integrating HUGGING FACE would connect models, datasets, notebooks, development environments and infrastructure.

GOOGLE CLOUD strengthened its partnership with the platform in 2025 to accelerate model downloads into VERTEX AI and GKE, provide native TPU support and add security features drawing in particular on MANDIANT.

An acquisition would give GOOGLE a lever similar to the one NVIDIA is seeking: making its accelerators almost as natural to use as GPUs for open models. But it would also create substantial overlap. KAGGLE already hosts datasets, notebooks and models. VERTEX AI MODEL GARDEN allows users to discover and deploy models. GOOGLE would have to decide which components to retain, merge or abandon, risking the gradual transformation of HUGGING FACE into a mere GOOGLE CLOUD interface when the Hub’s main advantage is precisely that it is not just another cloud product.

IBM may be the most compatible owner, but not the most generous

IBM represents a different case. Its primary interest would not be to sell more compute, but to make HUGGING FACE the open layer of WATSONX. The two companies have worked together since 2023 to allow enterprise customers to select, customise and deploy models from the community. IBM also publishes its own GRANITE models on HUGGING FACE.

The parallel with RED HAT is obvious. IBM could seek to preserve an open infrastructure, then sell support, governance, compliance, security and integration services around it. It would probably face less suspicion than NVIDIA, AMAZON or GOOGLE of trying to favour a particular computing architecture, while its experience with enterprise open source would give it a degree of legitimacy within the community.

But cultural compatibility is not enough to make an acquisition. At nearly $13 billion, IBM would have to demonstrate that it could generate sufficient additional revenue across WATSONX and its consulting business. The synergies would probably be more respectful of the Hub’s neutrality, but less immediate financially.

SALESFORCE could monetise governance rather than compute

SALESFORCE VENTURES led the 2023 funding round and already described HUGGING FACE as the centre connecting AI developers, researchers and practitioners.

For SALESFORCE, an acquisition could give AGENTFORCE and its enterprise applications privileged access to an extensive model library. Above all, the group could develop the functions large companies need to use open source: evaluation, licence control, security, version tracking, auditing and access management. The monetisation would come less from GPUs than from governance.

While this logic is consistent with the needs of SALESFORCE customers, it has two limitations. The group would capture less value from each computing workload than NVIDIA or AWS. And an overly tight integration with its CRM would narrow HUGGING FACE’s general-purpose remit.

AMD and INTEL would be the first losers from an NVIDIA acquisition

AMD and INTEL invested in HUGGING FACE for a simple reason: a model that is readily compatible with their processors is more likely to run on their infrastructure.

An NVIDIA acquisition of the Hub would not necessarily mean the end of those integrations. It would, however, change the incentives. NVIDIA would have an interest in ensuring that new models were optimised first for its GPUs, libraries and services.

AMD could theoretically make a counteroffer, but a deal approaching $13 billion would consume considerable resources without offering it the same monetisation opportunities as NVIDIA. INTEL appears even less likely to lead such a transaction.

Their main leverage may therefore be regulatory: securing equivalent support across different architectures, transparency in model recommendations and assurances that NVIDIA services receive no preferential treatment.

Model laboratories would make poor acquirers

OPENAI, ANTHROPIC, META or MISTRAL AI could also find a theoretical benefit in owning HUGGING FACE. They would gain global distribution, a technical community and a privileged channel for their models. But an acquisition would quickly destroy some of the value they were seeking.

Why would a competing laboratory continue publishing its models on a platform owned by META or OPENAI? Why would it share data on downloads, derivative models and user relationships there? HUGGING FACE would become the catalogue of a single producer rather than the common market for many.

META would be the most coherent candidate because of its open-weight strategy around LLAMA. But the platform would risk being perceived as an extension of that ecosystem. As for OPENAI and ANTHROPIC, whose strategies rely largely on proprietary models accessed through APIs, their culture and business models are less naturally aligned with HUGGING FACE’s historic mission.

The paradox of the ideal acquirer

The potential buyers do not, therefore, want exactly the same company.

NVIDIA wants a channel to GPUs.
MICROSOFT wants to extend GITHUB to models.
AMAZON wants to protect AWS workloads.
GOOGLE wants to open the Hub to TPUs.
IBM wants to distribute open source to businesses.
SALESFORCE wants to govern the models its customers use.

NVIDIA has the strongest industrial rationale and probably the greatest ability to justify the asking price. MICROSOFT offers the most coherent product integration. AMAZON has the strongest defensive interest. IBM may be the owner most compatible with the platform’s open culture.

Yet each faces the same contradiction: the more an acquirer uses HUGGING FACE to favour its own products, the greater the risk of driving away the players that give the Hub its value. The real issue is not simply who will control HUGGING FACE, but whether its future owner can remain discreet enough for the rest of the ecosystem to keep walking through the door.