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OpenAI and Anthropic face a spending crunch as companies cut AI costs, with Anthropic's annualized run rate at $47 billion and OpenAI's at $25 billion
| At a glance | |
|---|---|
| Anthropic's annualized run rate | $47 billion |
| OpenAI's annualized run rate | $25 billion |
| Lindy's expected savings | millions of dollars |
| Uber's AI budget | blown in four months |
The spending crunch is a result of the exponential growth of AI costs, which has led companies to reevaluate their AI spending. According to Gil Luria, an equity analyst at D.A. Davidson, "Current growth rates for Anthropic and OpenAI are the fastest they will ever be, which is mostly a matter of basic math" [1]. This has prompted companies like Uber to implement spending tiers on AI tools, starting at $1,500 per month. OpenAI and Anthropic have been trying to adjust to this new environment, with OpenAI launching analytics and updated controls for enterprises earlier this month [1].
The AI market is becoming increasingly competitive, with deep-pocketed companies like Microsoft, Amazon, and Google ramping up their investments in AI models. Microsoft has unveiled a suite of new low-cost models, while Amazon is developing models at a lower cost using its in-house chips [1]. This emerging competition is likely to put pressure on OpenAI and Anthropic to reduce their prices. According to Peter DeSantis, Amazon's top AI executive, "AI has a cost problem" [1].
| Comparison of AI models | |
|---|---|
| OpenAI's models | expensive, with no economies of scale |
| Microsoft's models | low-cost, with a focus on routing users to the most appropriate model |
| Amazon's models | developed using in-house chips, aiming to be more cost-effective |
The spending crunch facing OpenAI and Anthropic raises questions about the sustainability of their business models and the future of the AI market. As companies become more price-sensitive to AI, the competitive landscape is likely to shift, with emerging competitors aiming to develop lower-cost models. The real significance of this shift lies in its potential to disrupt the AI market and prompt a reassessment of the value proposition of AI models.
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AI-assisted synthesis by the TrendWatcher Editorial Desk · sourced from 3 outlets · Jun 26, 2026 · How we report
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