---
id: "verl-project-verl"
title: "verl (HybridFlow)"
creator: "verl project (originated at ByteDance Seed)"
creator_url: "https://github.com/verl-project/verl"
url: "https://github.com/verl-project/verl"
level: "expert"
level_max: null
category: "model-training"
subcategory: "post-training-rl"
region: "CN"
license: "open"
license_scope: "linked-resource"
models: ["any"]
source_date: null
date_added: "2026-10-18"
---

[Model Training](/model-training/index.md)

# verl (HybridFlow)

by [verl project (originated at ByteDance Seed)](https://github.com/verl-project/verl)

[Read the original →](https://github.com/verl-project/verl)

Explore how an RL training framework coordinates generation and optimization.

The verl project exposes a modular approach to post-training dataflows and distributed model execution. Its documentation is most useful to readers who already understand training loops and need to reason about infrastructure trade-offs.

Level: [Expert](/levels/index.md#expert)
Models: any
Category: [Model Training](/model-training/index.md)
Tags: 
Source date: date not stated
Added: 2026-10-18
Last verified: 2026-10-18
Status: ok
Prerequisites: Acts on model-training, infrastructure or research tooling; requires training-stack expertise.
Subcategory: [post training rl](/model-training/post-training-rl/index.md)
Region: CN
Original language: en
Access: free
Resource reuse: open: Source states Apache-2.0. Applies to the linked resource, not every referenced model or dataset. [Facet definitions](/about/index.md#facets)

Summary in our own words. Rights remain with the original creator. [Credit and correction policy](/about/index.md#credit-policy).

[Plain-text Markdown copy](/model-training/post-training-rl/verl-project-verl/index.md)