
Domain-adapted large language models, such as ChipNeMo, can provide significantly reduced total cost of ownership (up to 95%) compared to state-of-the-art general-purpose models, while maintaining comparable or superior performance in chip design coding assistance tasks.


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comparative-analysis-of-total-cost-of-ownership-and-performance-for-domain-adapted-large-language-models-versus-state-of-the-art-counterparts-in-chip-design-coding-assistance


Comparative Analysis of Total Cost of Ownership and Performance for Domain-Adapted Large Language Models versus State-of-the-Art Counterparts in Chip Design Coding Assistance
