Gorilla vs Langfuse
Side-by-side comparison of two AI agent tools
Short answer
- Gorilla has had no commit in 6 months; Langfuse is actively maintained (2,007 commits in the last 90 days).
- Langfuse is growing faster: +1,812 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 Langfuse for: open-source LLM engineering platform for observability, evaluation, prompt and dataset management.
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Gorillaopen-source
Gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls)
Langfuseopen-source
Open-source LLM engineering platform for observability, evaluation, prompt and dataset management
Metrics
| Gorilla | Langfuse | |
|---|---|---|
| Stars | 13.0k | 35.3k |
| Star velocity /mo | 41.111111111111114 | 1.8k |
| Commits (90d) | 0 | 2.0k |
| Releases (6m) | 0 | 10 |
| Overall score | 0.24387159309456813 | 0.9067292616632036 |
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
- +Open source with MIT license allowing full customization and transparency, plus active community support
- +Comprehensive feature set combining observability, prompt management, evaluations, and datasets in one platform
- +Extensive integrations with major LLM frameworks and tools including OpenTelemetry, LangChain, and OpenAI SDK
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
- -May require significant setup and configuration for self-hosted deployments
- -Could be overwhelming for simple use cases that only need basic LLM monitoring
- -Self-hosting requires technical expertise and infrastructure resources
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
- •Production LLM application monitoring to track performance, costs, and identify issues in real-time
- •Prompt engineering and management for teams collaborating on optimizing model prompts and tracking versions
- •LLM evaluation and testing to measure model performance across different datasets and use cases
FAQ
- Which is more popular, Gorilla or Langfuse?
- Langfuse has more GitHub stars (35,301 vs 13,043).
- Which is more actively developed, Gorilla or Langfuse?
- Langfuse had more commits in the last 90 days (2,007 vs 0).
- Should I use Gorilla or Langfuse?
- 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.