CodeQL vs AirLLM
A side-by-side comparison of features, pricing, and characteristics.
AirLLM
Open-source Python library that runs very large language models on low-memory GPUs by streaming model layers one at a time.
Read the full review| Attribute | CodeQL | AirLLM |
|---|---|---|
| Pricing type | Free + paid (from $49/mo) | Free |
| Korean support | No | No |
| Platforms | Web, CLI, API | Linux, macOS, CUDA-enabled NVIDIA GPUs, Apple Silicon |
| Open source | No | Yes |
| API available | Available | - |
| SDK | Available | - |
| LLM-based | - | - |
| Multimodal | - | - |
| AI model | GitHub Copilot for CodeQL, LLM-based query generation | Llama, Qwen, DeepSeek, Mistral, Mixtral, Phi, Gemma |
| GitHub Stars | 10.1K | 33.8K |
| Vendor | GitHub (acquired Semmle) | Anima AI LLC |
| Category | Developer Tools | Developer Tools |
| Details | View | View |
CodeQL key features
- Semantic Code Analysis
- Data Flow Analysis
- Taint Analysis
- Custom Query Writing
- GitHub Actions Integration
- Multi-language Support
AirLLM key features
- Reducing GPU memory usage through layer-wise model streaming
- Supporting inference of 70B-class models on a single 4GB GPU
- AutoModel interface based on Hugging Face model IDs
- 4-bit and 8-bit block-wise model compression
- Supporting CPU inference and Apple Silicon macOS
- Supporting various model families including Llama, Qwen, DeepSeek, and Mistral