Which is more popular, MLflow or Ragas?

MLflow has more GitHub stars (28,241 vs 15,913).

Which is more actively developed, MLflow or Ragas?

MLflow had more commits in the last 90 days (1,083 vs 0).

Should I use MLflow or Ragas?

Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.

MLflow vs Ragas

Side-by-side comparison of two AI agent tools

Short answer

Ragas has had no commit in 7 months; MLflow is actively maintained (1,083 commits in the last 90 days).
Pick MLflow for: open-source AI engineering platform for agents, LLMs, and ML models. Pick Ragas for: supercharge Your LLM Application Evaluations.

From GitHub data refreshed daily.

MLflowopen-source

Open-source AI engineering platform for agents, LLMs, and ML models

Ragasopen-source

Supercharge Your LLM Application Evaluations 🚀

Metrics

	MLflow	Ragas
Stars	28.2k	15.9k
Star velocity /mo	410	440.3684210526315
Commits (90d)	1.1k	0
Releases (6m)	10	0
Downloads (30d, npm + PyPI)	21.4M	—
Overall score	0.8184717317788615	0.3480794663399632

Pros

+提供客观的LLM应用评估指标，结合智能LLM评估和传统指标，确保评估结果的准确性和可靠性
+自动生成综合测试数据集功能，覆盖广泛应用场景，解决测试数据不足的问题
+与LangChain等主流框架深度集成，支持生产环境反馈循环，便于持续优化

Cons

-主要依赖Python生态系统，对其他编程语言的支持有限
-作为相对新兴的工具，社区生态和最佳实践仍在发展中
-LLM基础评估可能增加计算成本和延迟

Use Cases

•RAG系统性能评估：评估检索质量、答案准确性和相关性指标
•聊天机器人质量监控：自动评估对话质量、一致性和用户满意度
•LLM应用A/B测试：对比不同模型版本或提示策略的性能差异

View MLflow Details View Ragas Details

FAQ

Which is more popular, MLflow or Ragas?: MLflow has more GitHub stars (28,241 vs 15,913).
Which is more actively developed, MLflow or Ragas?: MLflow had more commits in the last 90 days (1,083 vs 0).
Should I use MLflow or Ragas?: Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.