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verl

Fine-Tuning 7.6/10 Strong

verl/HybridFlow: A Flexible and Efficient RL Post-Training Framework

verl scores 7.6/10 (Strong) in Fine-Tuning.

Language Python License Apache-2.0 Stars 22.3k★ Type heavyweight Self-host Yes Repo verl-project/verl Homepage https://verl.readthedocs.io

Quality

Strong 7.6
Adoption 59
Activity 90
Maturity 88
Community 66
Capability 50
Show the math
Overall 7.6/10
value = 7.6/10
score = value
Adoption 6.3/10
value = 58.7/100
score = 1 + 9 * value / 100
Activity 9.1/10
value = 90/100
score = 1 + 9 * value / 100
Maturity 8.9/10
value = 88/100
score = 1 + 9 * value / 100
Community 6.9/10
value = 65.7/100
score = 1 + 9 * value / 100
Capability 5.5/10
value = 50/100
score = 1 + 9 * value / 100

Key metrics

22.3k★ GitHub stars
404/90d Recent commits
65 devs/90d Recent contributors
1.7y Project age
active Last commit

Gotchas

No gotchas documented yet. Contribute one if you know a constraint we missed.

Labels

  • Self-hosted

    Self-hosted

    You deploy and operate it yourself; there is no hosted option here.

  • Heavyweight

    Heavyweight

    Resource-heavy to run (GPU, large memory, or multi-service stack).

rl grpo agentic-rl ray post-training