AI Potluck
Model components / Fine-tuning code

OpenPipe

OpenPipe

OpenPipe ships the open source Agent Reinforcement Trainer (ART, Apache-2.0, ~9.7K stars) alongside a closed managed prompt-logging and fine-tuning platform, an open-core stack for SFT and RL post-training of agents. Acquired by CoreWeave in September 2025 to anchor their RL-for-agents capability alongside Weights & Biases; ART continues active development as the open library, with the platform serving as the commercial wrapper.

Scored on ART (Agent Reinforcement Trainer), OpenPipe's open source fine-tuning/RL library (GRPO). v0.5.17 (Mar 13, 2026), confirmed live on GitHub June 2026. OpenPipe also runs a managed training/hosting platform on top of the OSS library.

Openness

4 high confidence
4.0
license
Apache-2.0(OSI, OpenPipe Inc.
source
public
methods
RL(GRPO)+SFT trajectory training
managed-tier
OpenPipe hosted training/serving SaaS on top of the OSS lib
core-gated
gated

Core ART library is OSI-licensed (Apache-2.0) and fully public; OpenPipe's revenue product is a managed training/hosting platform layered on top, so open_core.

Adoption

2 medium confidence
2.0

openpipe-art PyPI ~47.7k downloads last month; 9.9k GitHub stars (corroborating only). Specialist RL-fine-tuning audience; 10K-100K monthly-download band.

Capability

3 medium confidence
3.0

Capable, focused agent-RL trainer; mid-tier vs full training stacks (no TP/PP/EP at Megatron scale). Feature-matrix basis per recipe; no MLPerf-Training submission.

Unchanged since 2026-07-30 (last edited, not re-checked)