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Gartner projects over 90 percent drop in cost for trillion parameter LLM inference by 2030
Gartner forecasts that the cost for performing inference on a large language model with 1 trillion parameters will fall by more than 90 percent between 2025 and 2030.
This significant reduction is poised to reshape the economics for generative AI providers, potentially accelerating adoption and new capabilities. The trend reflects rapid advances in both model optimization and AI hardware innovation, which are expected to dramatically drive down operational expenses tied to large-scale deployments.
Gartner recently projected that artificial intelligence will manage half of HR functions by 2030, urging business leaders to adapt for competitiveness in a previous forecast. The company has also convened global finance leaders at its Finance Symposium Xpo 2026 in Sydney to address digital trends in corporate strategy. These events highlight Gartner's continued focus on technology-driven transformation in enterprise operations.
This material may contain third-party opinions, none of the data and information on this webpage constitutes investment advice according to our Disclaimer. While we adhere to strict Editorial Integrity, this post may contain references to products from our partners.
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