AirLLM vs Docling
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 reviewDocling
Docling is an open-source library by IBM Research that efficiently converts PDF and other document formats into Markdown or JSON.
Read the full review| Attribute | AirLLM | Docling |
|---|---|---|
| Pricing type | Free | Free |
| Korean support | No | No |
| Platforms | Linux, macOS, CUDA-enabled NVIDIA GPUs, Apple Silicon | Python Library, CLI, Docker |
| Open source | Yes | Yes |
| API available | - | Available |
| SDK | - | Available |
| LLM-based | - | - |
| Multimodal | - | - |
| AI model | Llama, Qwen, DeepSeek, Mistral, Mixtral, Phi, Gemma | Docling Layout Model, TableFormer |
| GitHub Stars | 33.8K | 66.0K |
| Vendor | Anima AI LLC | IBM Research |
| Category | Developer Tools | Developer Tools |
| Details | View | View |
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
Docling key features
- Multi-format support (PDF, DOCX, PPTX, HTML)
- Advanced table structure recognition
- Lightweight local AI models
- Markdown and JSON output
- Integrated OCR support
- Metadata and hierarchy preservation