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Decentralized large language model (LLM) inference networks are an exciting development in the Web3 space, taking inspiration from DeFi’s core principles. Instead of relying on centralized servers owned by big tech companies, these networks distribute AI processing across a global web of computers. This approach makes AI more affordable, censorship-resistant, and open to anyone, much like how DeFi empowers users by removing middlemen. By spreading the computational load, these networks aim to lower cost potentially by up to 80% compared to traditional cloud services while ensuring transparency and trust through blockchain technology.

DecentralGPT ($DGC) is one project pushing this vision forward. It’s a decentralized network where anyone with a GPU can contribute computing power to run AI models like DeepSeek or Qwen3, earning $DGC tokens as a reward. Developers can tap into this network to build AI-driven apps for things like DeFi trading tools, healthcare diagnostics, or educational platforms, all at a fraction of the cost of centralized alternatives. Regular users can also access powerful AI for tasks like writing, coding, or data analysis without high fees or geographic barriers. To protect privacy, DecentralGPT uses encryption to secure user data, and its blockchain foundation ensures transactions and operations are transparent.

The native token $DGC was listed on Bitget today and the price trend is looking good. This listing will increase exposure for the project, similar to how Bittensor ($TAO) gained traction. However, challenges like network latency, coordinating nodes, and ensuring data quality still need work. Despite these hurdles, the idea of a community-driven AI ecosystem is compelling. What do you think decentralized LLMs like this will become a key piece of Web3 infrastructure, or are they still too early to compete with centralized AI giants?

submitted by /u/Donsaudi29
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