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Running a One Trillion-Parameter LLM Locally on AMD Ryzen AI Max+ Cluster
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A small-scale distributed inference cluster can be built using AMD’s Ryzen™ AI Max+ AI PC platform to run a one trillion-parameter Large Language Model. A four-node cluster of Framework Desktop systems demonstrates the local inference of the Kimi K2.5 open-source model.
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Hacker News · amd.com
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- Praise: Running a one trillion-parameter LLM locally showcases significant advancements in AI capabilities, making high-performance models more accessible to enthusiasts.
- Praise: The ability to run such a large model on consumer hardware indicates a promising trend towards democratizing AI technology.
- Concern: Performance metrics reveal that the system struggles with low throughput (<10 tps) and high latency, making it impractical for real-time applications.
- Concern: The reported time-to-first-token of over a minute for an 8192 token prompt highlights severe inefficiencies compared to leading models like ChatGPT.
- Concern: The hardware's limitations, such as non-upgradable components and slow networking options, raise concerns about its long-term viability and usability.