AirLLM vs Langfuse
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 reviewLangfuse
Langfuse provides traces, evaluations, prompt management, and metrics to debug and improve LLM applications.
Read the full review| Attribute | AirLLM | Langfuse |
|---|---|---|
| Pricing type | Free | Free + paid (from $29/mo) |
| Korean support | No | Partial |
| Platforms | Linux, macOS, CUDA-enabled NVIDIA GPUs, Apple Silicon | CLI, Desktop, API |
| Open source | Yes | Yes |
| API available | - | Available |
| SDK | - | Available |
| LLM-based | - | Yes |
| Multimodal | - | Yes |
| AI model | Llama, Qwen, DeepSeek, Mistral, Mixtral, Phi, Gemma | GPT |
| GitHub Stars | 33.8K | 34.4K |
| Vendor | Anima AI LLC | Langfuse |
| 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
Langfuse key features
- LLM Observability and Tracing
- Prompt Management
- Evaluation and Datasets