Pu.sh vs AirLLM
A side-by-side comparison of features, pricing, and characteristics.
Pu.sh
A full coding-agent harness in 400 lines of shell. No npm. No pip. No Docker. Just curl, awk, and an API key.
Read the full reviewAirLLM
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 | Pu.sh | AirLLM |
|---|---|---|
| Pricing type | Free | Free |
| Korean support | No | No |
| Platforms | - | Linux, macOS, CUDA-enabled NVIDIA GPUs, Apple Silicon |
| Open source | No | Yes |
| API available | - | - |
| SDK | - | - |
| LLM-based | - | - |
| Multimodal | - | - |
| AI model | - | Llama, Qwen, DeepSeek, Mistral, Mixtral, Phi, Gemma |
| GitHub Stars | 229 | 33.8K |
| Vendor | Pu.sh | Anima AI LLC |
| Category | Developer Tools | Developer Tools |
| Details | View | View |
Pu.sh key features
- Lightweight harness in under 400 lines of shell script
- Zero-install setup requiring only curl and awk
- 7 core tools: bash, read, write, edit, grep, find, and ls
- Dual provider support for Anthropic and OpenAI APIs
- Interactive REPL and automatic context compaction
- Pipe mode for connecting multiple agent sessions
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