---
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id: "aa4e18d41776f95406ebb721e6d47685654fe186d2792bfd660ae5fcfaa99dd6"
canonical_url: "https://aidr.today/aa4e18d4?lang=en"
title: "Optimizing Agent Reliability and Tool Calling Efficiency for Chip Design Using NVIDIA NeMo Gym"
lang: "en"
requested_lang: "en"
available_langs: ["en","vi"]
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published_at: "2026-10-14T16:10:45.000Z"
category: "Frameworks"
topics: ["nvidia","agent","framework"]
source_urls: ["https://developer.nvidia.com/blog/optimizing-agent-reliability-and-tool-calling-efficiency-for-chip-design-using-nvidia-nemo-gym/"]
summary: "Siemens EDA used NVIDIA NeMo Gym to evaluate and improve the reliability of its Fuse EDA AI Agent, cutting agent turns by 66% and raising benchmark scores from 55% to 95%."
---

# Optimizing Agent Reliability and Tool Calling Efficiency for Chip Design Using NVIDIA NeMo Gym

> [Open the canonical story](<https://aidr.today/aa4e18d4?lang=en>)

**Published:** 2026-10-14T16:10:45.000Z
**Category:** Frameworks
**Topics:** nvidia, agent, framework

## Summary

Siemens EDA used NVIDIA NeMo Gym to evaluate and improve the reliability of its Fuse EDA AI Agent, cutting agent turns by 66% and raising benchmark scores from 55% to 95%\.

## Sources

- [Story source](<https://developer.nvidia.com/blog/optimizing-agent-reliability-and-tool-calling-efficiency-for-chip-design-using-nvidia-nemo-gym/>)