Gorilla vs Open Assistant API
Side-by-side comparison of two AI agent tools
Short answer
- Gorilla is growing faster: +41 GitHub stars in the last 30 days vs +1 for Open Assistant API.
- Pick Gorilla for: gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls). Pick Open Assistant API for: open-source, self-hosted AI assistant API compatible with OpenAI and supporting LLMs, RAG, and tools.
From GitHub data refreshed daily.
Gorillaopen-source
Gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls)
Open Assistant APIopen-source
Open-source, self-hosted AI assistant API compatible with OpenAI and supporting LLMs, RAG, and tools
Metrics
| Gorilla | Open Assistant API | |
|---|---|---|
| Stars | 13.0k | 367 |
| Star velocity /mo | 40.578947368421055 | 1.263157894736842 |
| Commits (90d) | 0 | 0 |
| Releases (6m) | 0 | 0 |
| Overall score | 0.22885397334190424 | 0.1576879918945088 |
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
- +开源自托管，提供完全的数据控制和隐私保护
- +通过 One API 集成支持更多 LLM 模型，不局限于 GPT
- +内置互联网搜索功能和 R2R RAG 引擎支持
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
- -代码解释器功能仍在开发中，不如 OpenAI 成熟
- -需要自行部署和维护，增加运维成本
- -需要一定的技术专业知识进行配置和部署
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
- •构建需要多种 LLM 模型支持的 AI 应用程序
- •开发需要互联网搜索能力的智能助手
- •企业级自托管 AI 助手解决方案部署
FAQ
- Which is more popular, Gorilla or Open Assistant API?
- Gorilla has more GitHub stars (13,041 vs 367).
- Which is more actively developed, Gorilla or Open Assistant API?
- Gorilla had more commits in the last 90 days (0 vs 0).
- Should I use Gorilla or Open Assistant API?
- 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.