Home/Compare/OpenRLHF vs LLM-Agent-Paper-List

Comparison

OpenRLHF vs LLM-Agent-Paper-List

Verdict

Pick OpenRLHF if openRLHF is a scalable and high-performance reinforcement learning framework from human feedback, built on Ray for distributed scheduling and vLLM for efficient inference, supporting models up to 70B+ parameters; pick LLM-Agent-Paper-List if lLM-Agent-Paper-List is a curated repository of essential papers on large language model-based agents, focusing on AgentGym, a framework for developing and training LLM agents through.

Markdown twin · OpenRLHF alternatives · LLM-Agent-Paper-List alternatives

GraphCanon updated Sep 20, 2026

8views this month

OpenRLHF logo

OpenRLHF

OpenRLHF/OpenRLHF

★ 10kpushed Sep 17, 2026
vs
LLM-Agent-Paper-List logo

LLM-Agent-Paper-List

WooooDyy/LLM-Agent-Paper-List

★ 8.2kpushed Sep 12, 2025

Trust & integrity

SignalOpenRLHFLLM-Agent-Paper-List
Maintenance
Very active (1d since push)
As of Sep 18, 2026 · github_public_v1
Dormant (371d since push)
As of Sep 18, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 18, 2026 · github_public_v1
Not a fork · Personal account
As of Sep 18, 2026 · github_public_v1
OSV dependency advisories
Published findings
As of Sep 18, 2026 · osv@v1
No lockfile (source not queried)
As of Sep 18, 2026 · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

OpenRLHF
Scalable and High-performance Agentic RL Framework based on Ray
LLM-Agent-Paper-List
Must-read papers for LLM-based agents.

Stars

OpenRLHF
10k
LLM-Agent-Paper-List
8.2k

Forks

OpenRLHF
1.0k
LLM-Agent-Paper-List
499

Open issues

OpenRLHF
380
LLM-Agent-Paper-List
32

Language

OpenRLHF
Python
LLM-Agent-Paper-List
-

Adopt for

OpenRLHF
OpenRLHF is a scalable and high-performance reinforcement learning framework from human feedback, built on Ray for distributed scheduling and vLLM for efficient inference, supporting models up to 70B+ parameters.
LLM-Agent-Paper-List
LLM-Agent-Paper-List is a curated repository of essential papers on large language model-based agents, focusing on AgentGym, a framework for developing and training LLM agents through reinforcement learning.

Persona

OpenRLHF
-
LLM-Agent-Paper-List
-

Runtime

OpenRLHF
-
LLM-Agent-Paper-List
-

License

OpenRLHF
Apache-2.0
LLM-Agent-Paper-List
-

Last pushed

OpenRLHF
Sep 17, 2026
LLM-Agent-Paper-List
Sep 12, 2025

Categories

OpenRLHF
Inference & Serving, Model Training
LLM-Agent-Paper-List
AI Agents, Evaluation & Observability, Model Training

Trust and health

Maintenance

OpenRLHF
Very active (96%)
LLM-Agent-Paper-List
Dormant (18%)

Days since push

OpenRLHF
1d
LLM-Agent-Paper-List
371d

Open issues (now)

OpenRLHF
380
LLM-Agent-Paper-List
32

Stars delta

OpenRLHF
+123 (30d)
LLM-Agent-Paper-List
+50 (30d)

Open issues delta

OpenRLHF
+13 (30d)
LLM-Agent-Paper-List
+1 (30d)

Owner type

OpenRLHF
Organization
LLM-Agent-Paper-List
User

OSV dependency advisories

OpenRLHF
Published findings
LLM-Agent-Paper-List
No lockfile (source not queried)

Full report

OpenRLHF
Trust report
LLM-Agent-Paper-List
Trust report

Choose OpenRLHF if…

  • Tags unique to OpenRLHF: proximal-policy-optimization, raylib, reinforcement-learning-from-human-feedba, transformers.
  • Also covers Inference & Serving.
  • When you need to train large models up to 70B+ parameters with efficient distributed scheduling and high-performance inference.

When NOT to use OpenRLHF

  • If your project does not require support for large models or distributed training, as OpenRLHF's complexity and resource requirements may be unnecessary.
  • When you prefer a framework that does not rely on Ray for distributed scheduling, as OpenRLHF's architecture is tightly coupled with Ray for its distributed capabilities.

Choose LLM-Agent-Paper-List if…

  • Tags unique to LLM-Agent-Paper-List: agent, evaluation, llm, nlp.
  • Also covers AI Agents, Evaluation & Observability.
  • When you need a comprehensive list of must-read papers on LLM-based agents, including detailed insights into AgentGym, a framework for developing and training LLM agents through reinforcement learning

When NOT to use LLM-Agent-Paper-List

  • If you are looking for a tool that focuses on a broader range of AI agent development beyond LLM-based agents, as LLM-Agent-Paper-List is specifically curated for LLM-based agents
  • When you need real-time updates or a dynamic list of papers, as the repository is a static list and does not automatically update with new publications
  • If you require a tool that includes practical code implementations for all listed papers, as the repository primarily serves as a list and does not provide comprehensive code for every paper

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: OpenRLHF 10k · LLM-Agent-Paper-List 8.2k (synced Sep 20, 2026).

Common questions

What is the difference between OpenRLHF and LLM-Agent-Paper-List?
OpenRLHF: Scalable and High-performance Agentic RL Framework based on Ray. LLM-Agent-Paper-List: Must-read papers for LLM-based agents.. See the comparison table for live GitHub stats and shared categories.
When should I choose OpenRLHF over LLM-Agent-Paper-List?
Choose OpenRLHF over LLM-Agent-Paper-List when Tags unique to OpenRLHF: proximal-policy-optimization, raylib, reinforcement-learning-from-human-feedba, transformers; Also covers Inference & Serving; When you need to train large models up to 70B+ parameters with efficient distributed scheduling and high-performance inference.
When should I choose LLM-Agent-Paper-List over OpenRLHF?
Choose LLM-Agent-Paper-List over OpenRLHF when Tags unique to LLM-Agent-Paper-List: agent, evaluation, llm, nlp; Also covers AI Agents, Evaluation & Observability; When you need a comprehensive list of must-read papers on LLM-based agents, including detailed insights into AgentGym, a framework for developing and training LLM agents through reinforcement learning.
When should I avoid OpenRLHF?
If your project does not require support for large models or distributed training, as OpenRLHF's complexity and resource requirements may be unnecessary. When you prefer a framework that does not rely on Ray for distributed scheduling, as OpenRLHF's architecture is tightly coupled with Ray for its distributed capabilities.
When should I avoid LLM-Agent-Paper-List?
If you are looking for a tool that focuses on a broader range of AI agent development beyond LLM-based agents, as LLM-Agent-Paper-List is specifically curated for LLM-based agents When you need real-time updates or a dynamic list of papers, as the repository is a static list and does not automatically update with new publications If you require a tool that includes practical code implementations for all listed papers, as the repository primarily serves as a list and does not provide comprehensive code for every paper
Is OpenRLHF or LLM-Agent-Paper-List more popular on GitHub?
OpenRLHF has more GitHub stars (10,014 vs 8,222). Stars measure visibility, not whether either tool fits your constraints.
Are OpenRLHF and LLM-Agent-Paper-List open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to OpenRLHF or LLM-Agent-Paper-List?
GraphCanon lists graph-backed alternatives at OpenRLHF alternatives and LLM-Agent-Paper-List alternatives (OpenRLHF markdown twin, LLM-Agent-Paper-List markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, OpenRLHF or LLM-Agent-Paper-List?
OpenRLHF: Very active. LLM-Agent-Paper-List: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for OpenRLHF and LLM-Agent-Paper-List?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: OpenRLHF trust report; LLM-Agent-Paper-List trust report.

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