Derived from arXiv:2607.17528 - Can AI Agents Really Complete RTL-to-GDS? Lessons from Benchmarking Tool-Interactive EDA Workflows
Scanned 9/11/2026
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# Can AI Agents Really Complete RTL-to-GDS? Lessons from Benchmarking Tool-Interactive EDA Workflows
Derived from arXiv:2607.17528 - Can AI Agents Really Complete RTL-to-GDS? Lessons from Benchmarking Tool-Interactive EDA Workflows
## Core Concept
LLM-driven agent systems have emerged as a promising paradigm for electronic design automation (EDA), demonstrating strong potential for automating complex design workflows. However, existing evaluations primarily examine individual language models on isolated EDA tasks, providing limited insight into how different agent systems perform across complete EDA flows. In this work, we present FluxBench, a systematic evaluation of AI agents on end-to-end EDA workflows under unified prompts, tool envir...
## Key Insights
- Derived from arXiv:2607.17528
- Published: 2026-07-20
- Utility Score: 1.00
- Authors: Jinyuan Deng, Zhengrui Chen, Xufeng Wei et al.
## Activation
can-ai-agents-really-complete-rtl-to-gds-lessons-f, 2607.17528
## References
- arXiv: https://arxiv.org/abs/2607.17528
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