AReaL Project

license

Apache-2.0(OSI)

source

public(areal-project/AReaL)

core features withheld

no — no enterprise or ee path in the repository root and no paid tier described in the README

Apache-2.0, an OSI license, with the full source public in this repository. There is no enterprise or ee path in the repository and no paid tier described in the README.

• https://raw.githubusercontent.com/areal-project/AReaL/main/LICENSE recorded 2026-10-07

  LICENSE body, read in full: the stock Apache License 2.0 text, carrying no appended term or additional condition.

• https://raw.githubusercontent.com/areal-project/AReaL/main/README.md recorded 2026-10-07

  README, read for the distribution and gating question: it installs and runs the code from this repository with "uv sync --extra cuda", which "installs training packages + SGLang (default inference backend)", and names no enterprise, pricing, paid or licence-gated build.

AReaL's only PyPI release, 1.0.4, was uploaded 2026-06-10; the repository has since moved to the current v2.1.0 line, released 2026-08-25, so a download count from the old package measures a version the project has already left behind rather than current use. No stronger usage signal is available: GitHub stars reflect attention rather than use, so the level stays where it was.

• https://api.github.com/repos/areal-project/AReaL recorded 2026-08-31

  Repo metadata for areal-project/AReaL: stargazers_count 5705, archived false, pushed_at 2026-08-31 - the attention figure the note contrasts with the download count.

• https://api.github.com/repos/areal-project/AReaL/releases/latest recorded 2026-08-31

  tag_name v2.1.0, published_at 2026-08-25T10:23:59Z, prerelease false - the current stable release line, one major above the sole PyPI release.

• https://pypi.org/pypi/areal/json recorded 2026-08-31

  info.version 1.0.4 with a single entry in `releases`, uploaded 2026-06-10T06:48:31Z. The package has made no other release, so the registry line has never moved past 1.x while the repository is on 2.1.0.

• https://pypistats.org/api/packages/areal/recent recorded 2026-08-31

  last_month 45, last_week 9, last_day 3 for the areal package. Recorded as a measurement of the trailing registry line, explicitly NOT as the basis of the reading.

AReaL matches OpenRLHF's breadth: several RL algorithms running over FSDP or Megatron training with vLLM or SGLang rollout, scaled across tensor, pipeline and expert parallelism. It covers the same ground from a different angle, asynchronous agentic RL rather than OpenRLHF's Ray-scheduled RLHF at 70B and above, and neither reaches the wider method catalog of verl or nemo-rl.

• https://raw.githubusercontent.com/areal-project/AReaL/main/README.md recorded 2026-10-07

  README describes "A Large-Scale Asynchronous Reinforcement Learning System" built on a fully asynchronous RL paradigm, a "Support Matrix" with Algorithms (GRPO, GSPO, PPO, DAPO, DPO, SFT among them), Models, "Training Backends" and "Inference Backends" tables, and example sets for Math & Reasoning, "Agentic RL" and "Vision-Language Models".