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NVIDIA Unveils NOOA, a Framework That Builds Agents as Python Classes

Research preview argues harness design determines benchmark performance, released as open source

NVIDIA Unveils NOOA, a Framework That Builds Agents as Python Classes

Summary

  • NVIDIA Labs has released NOOA, an open-source framework that structures agents as a single Python class, as a research preview.
  • Methods map to capabilities, fields to state, and docstrings to prompts, with type annotations serving as contracts.
  • The company said the framework showed higher accuracy and lower token costs than existing harnesses on the SWE-bench Verified, CyberGym L1, and ARC-AGI-3 benchmarks.

NVIDIA Labs has released "NOOA (NVIDIA Labs Object-Oriented Agents)," an open-source framework that defines AI agents as a single Python class, as a research preview. The work is authored by Ricardo Silveira Cabral and Paul Furgale, and was published on the NVIDIA Developer Blog on July 27, 2026.

NVIDIA Unveils NOOA, a Framework That Builds Agents as Python Classes
이미지: NVIDIA Dev Blog
NVIDIA Unveils NOOA, a Framework That Builds Agents as Python Classes
이미지: NVIDIA Dev Blog

Treating agents like code

In NOOA, an agent's methods serve as its capabilities, its fields as its state, and its docstrings as its prompts. Type annotations function as enforced contracts, and methods whose bodies are marked with an ellipsis (…) are filled in and executed at runtime by an LLM-driven loop. NVIDIA explained that this approach makes agent development resemble ordinary software development, allowing both humans and AI coding agents to use existing tools for diffing, code review, unit testing, and version control.

On the memory management side, the framework accumulates typed, relational long-term memory in a human-readable SQLite store, and manages context efficiently through pass-by-reference, eliminating the need for separate context compression or summarization pipelines, according to NVIDIA.

NVIDIA said NOOA achieved higher accuracy and lower token costs than existing harnesses across three benchmarks: SWE-bench Verified, CyberGym L1, and ARC-AGI-3. The company released the code, data, and evaluation methodology together to allow the community to reproduce and verify the results.

NVIDIA Unveils NOOA, a Framework That Builds Agents as Python Classes
이미지: NVIDIA Dev Blog

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