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Large language models (LLMs) have shown strong potential for transforming hardware design through natural language interaction. However, existing methods often struggle with code quality, error handling, and design optimization. We propose ChipClaude, a hardware design framework that integrates Claude 3.7 Sonnet’s advanced reasoning capabilities, 200K-token context window, and distilled domain knowledge to generate high-quality HDL code from natural language specifications. ChipClaude utilizes a four-stage pipeline consisting of hierarchical prompt engineering, verifiable code generation, integrated formal verification, and multi-objective design optimization. Experimental results demonstrate a 22% improvement in first-pass success rate, a 74% reduction in manual corrections, and up to 47% better Power-Performance-Area (PPA) optimization for complex designs. These results highlight ChipClaude’s effectiveness in scaling natural language hardware design.

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ChipClaude: A Framework for Natural Language-Based Hardware Design Using LLM Distillation

  • 会议论文

  • 发表日期：

    2026年

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  • Tung Vu,
  • Quang Dang,
  • Phuong Anh Nguyen,
  • Ngoc Le

摘要

Large language models (LLMs) have shown strong potential for transforming hardware design through natural language interaction. However, existing methods often struggle with code quality, error handling, and design optimization. We propose ChipClaude, a hardware design framework that integrates Claude 3.7 Sonnet’s advanced reasoning capabilities, 200K-token context window, and distilled domain knowledge to generate high-quality HDL code from natural language specifications. ChipClaude utilizes a four-stage pipeline consisting of hierarchical prompt engineering, verifiable code generation, integrated formal verification, and multi-objective design optimization. Experimental results demonstrate a 22% improvement in first-pass success rate, a 74% reduction in manual corrections, and up to 47% better Power-Performance-Area (PPA) optimization for complex designs. These results highlight ChipClaude’s effectiveness in scaling natural language hardware design.