NVIDIA open-sources Molt, a PyTorch-native framework for agentic RL
nvidia · hf · 2026-07-27
- NVIDIA introduces Molt, a PyTorch-native training framework for agentic reinforcement learning.
- The framework is designed to keep the codebase compact and easy to reason about, so researchers—and AI coding assistants—can trace and modify the full algorithm flow end to end.
- It uses a single asynchronous loop to train multimodal and mixture-of-experts policies, while keeping tokens, policy versions, and model semantics consistent.
- NVIDIA says Molt is statistically comparable to a state-of-the-art Megatron-based stack under a matched fully asynchronous protocol.
- The project is open source, with recipes and containers published on GitHub.
Related event: NVIDIA Open-Sources Molt Framework for Agentic Reinforcement Learning(3 posts)→
More from coding & agent
- Goal-driven AI needs verifiable success signals, or it invents its own — daniel_mac8 · 2026-09-11
- Frontier models need ways to verify success — or they'll invent their own — daniel_mac8 · 2026-09-11
- Sakana AI launches Fugu Max: dynamic multi-agent routing across its largest open-model pool — graceisford · 2026-09-11
- Is inference latency becoming the biggest bottleneck for production AI agents? — Euphoric_Sea632 · 2026-09-11
- Anthropic researcher: 99% of engineers now run swarms of 300+ self-improving agents — AlishaOutridge · 2026-09-11
- Gergely Orosz: Shipping 10x PRs With AI Agents, Sites Fill With Small Regressions — ducha_aiki · 2026-09-11