The Coming Cooldown of the LLM Hype
Clem Delangue, the co-founder and CEO of Hugging Face, believes the industry isn’t experiencing an AI bubble as many fear, but rather an overinflated moment specifically around large language models — one he thinks may soon deflate.
Speaking at an Axios event, he acknowledged that debates about whether a bubble exists are enormously important, but argued that even if the hype around LLMs cools down, the broader field of artificial intelligence will remain strong.
Delangue explained that the spotlight has been disproportionately centered on LLMs like those behind major chatbot systems, and he expects that level of intense focus to fade over time.
He remarked that the current enthusiasm surrounding LLMs looks unsustainable and predicted that this subset of AI could experience a correction as early as next year, while other areas of the field continue accelerating.
One of his concerns is that LLMs are often treated as universal solutions, even though many tasks would be better handled by smaller, domain-specific models designed for particular needs.
According to Delangue, investors and companies have poured enormous amounts of attention and funding into the idea that a single, massive model can meet every requirement for every user — a belief he says the market will eventually move past.
To illustrate the shift he anticipates, he brought up the example of automated customer support for banks.
In those scenarios, he said, businesses don’t need a system capable of answering philosophical questions. Instead, a compact model optimized for banking workflows would be cheaper, faster, and easier for companies to run on their own infrastructure.
Why Hugging Face Is Taking a Long-Term Approach
Delangue acknowledged that a downturn in LLM hype could affect Hugging Face to a certain degree, but emphasized that the AI ecosystem is broad enough that such a shift wouldn’t threaten the overall health of the company or the field.
He also highlighted that Hugging Face still retains roughly half of the $400 million it has raised, which reflects a more cautious, disciplined spending strategy compared with other organizations racing to dominate the LLM market.
Delangue joked that by today’s standards, this level of restraint practically counts as profitability, especially since some competitors burn through billions rather than hundreds of millions.
In contrast, his company is deliberately choosing an approach that prioritizes long-term efficiency over aggressive, high-cost expansion.
He noted that many firms seem to be operating in a panic, chasing quick wins, whereas his 15 years in AI have taught him the importance of learning from past cycles and building a durable, meaningful business for the future.
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