In February, AI coding startup Windsurf was reportedly in talks to raise a large new funding round at a $2.85 billion valuation led by Kleiner Perkins. This valuation was roughly double what the company had achieved just six months earlier. However, according to a source familiar with the situation, that funding deal ultimately did not materialize.
Instead, news emerged in April that Windsurf was planning to sell itself to OpenAI for around $3 billion. Despite the high-profile nature of this potential acquisition, the deal famously fell through and did not come to fruition.
A bigger question remains as to why a fast-growing startup attracting significant venture capital interest would consider selling at all. Windsurf, in particular, has an expensive cost structure that results in very negative gross margins, meaning it costs more to run the product than the startup can generate in revenue.
One of the main cost drivers is the expense of using large language models (LLMs). AI coding assistants must offer the latest, most advanced, and often most costly LLMs, as model developers constantly fine-tune these models to improve coding-related tasks like writing and debugging code. These costs weigh heavily on startups trying to compete in the vibe-coding and code-assistant market.
Competition is fierce, with rivals such as Anysphere’s Cursor and Microsoft’s GitHub Copilot already having large customer bases. Because of this, startups like Windsurf face pressure not only on product capabilities but also on costs.
The most straightforward way for these companies to improve their margins is to develop their own AI models in-house. By doing so, they can avoid the high fees associated with paying external suppliers like Anthropic or OpenAI.
“It’s a very expensive business to run if you’re not going to be in the model game,” one insider emphasized, highlighting the critical importance of owning the underlying AI technology to achieve sustainable profitability.
Source: Doe, J. The high costs and thin margins threatening AI coding startups. TechCrunch.
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