Artificial Intelligence

Anthropic Is Too Expensive, Microsoft's AI Chief Warns — US Firms Turn to China's DeepSeek

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Anthropic Is Too Expensive, Microsoft's AI Chief Warns — US Firms Turn to China's DeepSeek

Microsoft AI Chief Mustafa Suleyman criticized Anthropic’s pricing as too expensive, prompting US firms to explore cheaper alternatives like China’s DeepSeek, which offers lower costs and open-source flexibility. DeepSeek’s valuation has surged to $60 billion, while its resource-efficient models and customizable deployment are driving adoption despite geopolitical data concerns.

Microsoft AI Chief Mustafa Suleyman has warned that Anthropic’s subscription costs are prohibitive, pushing US companies toward more affordable AI solutions. Anthropic’s Pro package costs $20 per month, while its Max bundle is $100 monthly, making scaling expensive for large organizations. Suleyman stated Microsoft aims to reduce reliance on Anthropic, particularly after launching seven new MAI models at its Build conference, claiming one matches Anthropic’s Opus 4.6 capabilities at a lower price. Despite Microsoft’s efforts, US firms are increasingly turning to Chinese AI models like DeepSeek to cut costs. Owned by High-Flyer, a Chinese hedge fund, DeepSeek has gained traction with a reported $60 billion valuation. Analyst Ara Kharazian noted that companies are willing to use cheaper Chinese models, even if it involves sending data to China-hosted servers. DeepSeek’s appeal extends beyond pricing—its open-source models allow companies to customize and deploy AI on their own infrastructure, reducing dependency on external providers. The platform also optimizes models to run efficiently on fewer resources while maintaining performance. This approach has inspired other Chinese firms to offer lighter, more affordable alternatives to US-based competitors. While DeepSeek is currently rising in popularity, competition from platforms like Fireworks AI, Fal AI, and DeepInfra could shift market interest. Kharazian cautioned that trends may change based on features and innovation, but cost remains a key driver for adoption. The shift highlights broader concerns about balancing affordability with data security in AI integration.

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