AnalogSAGE: AI for Analog Circuit Design
Paper#AI in Circuit Design🔬 Research|Analyzed: Jan 3, 2026 16:29•
Published: Dec 27, 2025 02:06
•1 min read
•ArXivAnalysis
This paper introduces AnalogSAGE, a novel multi-agent framework for automating analog circuit design. It addresses the limitations of existing LLM-based approaches by incorporating a self-evolving architecture with stratified memory and simulation-grounded feedback. The open-source nature and benchmark across various design problems contribute to reproducibility and allow for quantitative comparison. The significant performance improvements (10x overall pass rate, 48x Pass@1, and 4x reduction in search space) demonstrate the effectiveness of the proposed approach in enhancing the reliability and autonomy of analog design automation.
Key Takeaways
- •AnalogSAGE is a self-evolving multi-agent framework for analog circuit design.
- •It utilizes stratified memory and simulation-grounded feedback.
- •The framework is open-source and benchmarked on various design problems.
- •It significantly outperforms existing approaches in terms of pass rate and search space reduction.
Reference / Citation
View Original"AnalogSAGE achieves a 10$ imes$ overall pass rate, a 48$ imes$ Pass@1, and a 4$ imes$ reduction in parameter search space compared with existing frameworks."