AirLLM vs Trieve
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 reviewTrieve
Trieve provides infrastructure for search teams building retrieval and RAG applications.
Read the full review| Attribute | AirLLM | Trieve |
|---|---|---|
| Pricing type | Free | Free + paid (from $5/mo) |
| Korean support | No | No |
| Platforms | Linux, macOS, CUDA-enabled NVIDIA GPUs, Apple Silicon | web, desktop, api |
| Open source | Yes | Yes |
| API available | - | - |
| SDK | - | - |
| LLM-based | - | Yes |
| Multimodal | - | - |
| AI model | Llama, Qwen, DeepSeek, Mistral, Mixtral, Phi, Gemma | GPT, Jina, SPLADE, BGE |
| GitHub Stars | 33.8K | 2.7K |
| Vendor | Anima AI LLC | Trieve |
| 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
Trieve key features
- Semantic full-text hybrid search
- RAG and retrieval infrastructure
- Relevancy tuning and ranking tools