Which is more popular, Gorilla or MLflow?

MLflow has more GitHub stars (28,232 vs 13,043).

Which is more actively developed, Gorilla or MLflow?

MLflow had more commits in the last 90 days (1,072 vs 0).

Should I use Gorilla or MLflow?

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.

Gorilla vs MLflow

Side-by-side comparison of two AI agent tools

Short answer

Gorilla has had no commit in 6 months; MLflow is actively maintained (1,072 commits in the last 90 days).
MLflow is growing faster: +480 GitHub stars in the last 30 days vs +41 for Gorilla.
Pick Gorilla for: gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls). Pick MLflow for: open-source AI engineering platform for agents, LLMs, and ML models.

From GitHub data refreshed daily.

Gorillaopen-source

Gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls)

MLflowopen-source

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

Metrics

	Gorilla	MLflow
Stars	13.0k	28.2k
Star velocity /mo	41.111111111111114	480
Commits (90d)	0	1.1k
Releases (6m)	0	10
Overall score	0.24387159309456813	0.8404951044062294

Pros

+提供业界领先的Berkeley Function Calling Leaderboard，为LLM工具调用能力评估设立标准
+支持复杂的多轮对话和多步骤函数调用评估，包含状态管理和错误恢复机制
+活跃的学术研究社区，持续更新评估方法和数据集，与LMSYS等知名平台合作

Cons

-主要面向研究用途，对于生产环境的实际应用指导有限
-文档信息不够完整，缺乏详细的实施和部署指南

Use Cases

•AI研究人员评估和比较不同LLM的函数调用能力表现
•开发团队基准测试自己的AI智能体在复杂工具集成场景中的性能
•学术机构研究多模态AI系统在真实世界任务中的工具使用效果

View Gorilla Details View MLflow Details

FAQ

Which is more popular, Gorilla or MLflow?: MLflow has more GitHub stars (28,232 vs 13,043).
Which is more actively developed, Gorilla or MLflow?: MLflow had more commits in the last 90 days (1,072 vs 0).
Should I use Gorilla or MLflow?: 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.