chinese-llm-benchmark logo
chinese-llm-benchmark
★ 6.5k
vs
verl-agent logo
verl-agent
★ 2.4k

chinese-llm-benchmark vs verl-agent

chinese-llm-benchmark: ReLE Benchmark (formerly CLiB) provides a continuously updated evaluation for Chinese AI large language models, covering over 337 commercial and open-source LLMs. It offers multi-dimensional capability assessments across various domains, along with comprehensive rankings and a large defect library for model improvement.; verl-agent: `verl-agent` extends veRL to train LLM agents using reinforcement learning, featuring a novel step-independent multi-turn rollout mechanism. This design ensures high scalability for long-horizon tasks by allowing customizable per-step input structures and memory management.

01

TL;DR

chinese-llm-benchmark logo
chinese-llm-benchmarkLLM Infra · ★ 6.5k

Comparing and selecting the best performing LLMs for specific applications.

verl-agent logo
verl-agentLLM Infra · ★ 2.4k

Training large language model agents for complex multi-turn, long-horizon tasks.

02

Side-by-Side Comparison

Field
chinese-llm-benchmark logochinese-llm-benchmark
verl-agent logoverl-agent
Category
LLM Infra
LLM Infra
Stars
★ 6.5k
★ 2.4k
License
—
Apache-2.0
Install Command
git clone https://github.com/jeinlee1991/chinese-llm-benchmark.git
pip install -e .
Updated
1d ago
4mo ago
Open Source
Yes
Yes
Tags
LLM Evaluation, Chinese LLMs, AI Benchmark
LLM Agents, Reinforcement Learning, Deep Learning
03

Features

chinese-llm-benchmark logochinese-llm-benchmark
01Extensive coverage of 337+ commercial and open-source Chinese LLMs.
02Multi-dimensional evaluation across 7 main domains and ~300 sub-dimensions.
03Provides detailed ranking lists for various capabilities and specific domains.
04Offers a large defect library with over 2 million LLM flaws for research and improvement.
05Supports customized model selection and free evaluation services for private models.
verl-agent logoverl-agent
01Multi-Turn Agent-Environment Interaction
02Fully Customizable Memory Module & Per-Step Input Structure
03Scalable for Very Long-Horizon Optimization
04Parallelized Gym-Style Environments and Group Environments
05Diverse Reinforcement Learning Algorithms
04

Use Cases

chinese-llm-benchmark logochinese-llm-benchmark
↳Comparing and selecting the best performing LLMs for specific applications.
↳Identifying weaknesses and improving the capabilities of large language models.
↳Benchmarking private or custom LLMs against public models for performance and cost optimization.
verl-agent logoverl-agent
↳Training large language model agents for complex multi-turn, long-horizon tasks.
↳Developing reasoning agents for both visual and text-based environments.
↳Solving digital interface control, embodied AI, and search-related challenges.
05

Best For

chinese-llm-benchmark logochinese-llm-benchmark
EssentialTrending
verl-agent logoverl-agent
—
FAQ

FAQ

What is the difference between chinese-llm-benchmark and verl-agent?
Both chinese-llm-benchmark and verl-agent are in the LLM Infra category. chinese-llm-benchmark has 6.5k stars, while verl-agent has 2.4k stars.
Which is better, chinese-llm-benchmark or verl-agent?
The best choice depends on your use case. Choose chinese-llm-benchmark if Comparing and selecting the best performing LLMs for specific applications., and verl-agent if Training large language model agents for complex multi-turn, long-horizon tasks..
Is chinese-llm-benchmark free or open source?
Yes, chinese-llm-benchmark is open source on GitHub.
Is verl-agent free or open source?
Yes, verl-agent is open source on GitHub (Apache-2.0).
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