llama.cpp vs smolagents
Side-by-side comparison of two AI agent tools
Short answer
- llama.cpp is growing faster: +4,833 GitHub stars in the last 30 days vs +531 for smolagents.
- Pick llama.cpp for: lLM inference in C/C++. Pick smolagents for: smolagents: a barebones library for agents that think in code.
From GitHub data refreshed daily.
llama.cppopen-source
LLM inference in C/C++
smolagentsopen-source
π€ smolagents: a barebones library for agents that think in code.
Metrics
| llama.cpp | smolagents | |
|---|---|---|
| Stars | 130.2k | 29.7k |
| Star velocity /mo | 4.8k | 531 |
| Commits (90d) | 1.5k | 10 |
| Releases (6m) | 10 | 2 |
| Overall score | 0.9144269769694128 | 0.625603384872754 |
Pros
- +High-performance C/C++ implementation optimized for local inference with minimal resource overhead
- +Extensive model format support including GGUF quantization and native integration with Hugging Face ecosystem
- +Multiple deployment options including CLI tools, REST API server, Docker containers, and IDE extensions
- +Code-first agent approach provides precise control over agent actions compared to natural language-based systems
- +Extremely lightweight architecture with core logic in ~1,000 lines of code, making it easy to understand and customize
- +Multiple sandboxed execution options ensure secure code execution in production environments
Cons
- -Requires technical knowledge for compilation and model conversion processes
- -Limited to inference only - no training capabilities
- -Frequent API changes may require code updates for downstream applications
- -Limited documentation in the provided source, potentially creating learning curve for new users
- -Code-based approach may require more programming knowledge compared to natural language agent frameworks
- -Dependency on external sandbox providers (Blaxel, E2B, Modal) for secure execution may add complexity
Use Cases
- β’Local AI inference for privacy-sensitive applications without cloud dependencies
- β’Code completion and development assistance through VS Code and Vim extensions
- β’Building AI-powered applications with REST API integration via llama-server
- β’Building AI agents that need to perform precise code-based actions like data analysis, file manipulation, or API integrations
- β’Developing secure agent systems where code execution must be isolated in sandboxed environments
- β’Creating shareable agent tools and workflows that can be distributed through the Hugging Face Hub ecosystem
FAQ
- Which is more popular, llama.cpp or smolagents?
- llama.cpp has more GitHub stars (130,194 vs 29,662).
- Which is more actively developed, llama.cpp or smolagents?
- llama.cpp had more commits in the last 90 days (1,501 vs 10).
- Should I use llama.cpp or smolagents?
- 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.