AirLLM vs vLLM

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.

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vLLM

vLLM is a high-throughput and memory-efficient open-source library for LLM inference and serving.

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AttributeAirLLMvLLM
Pricing typeFreeFree
Korean supportNoYes
PlatformsLinux, macOS, CUDA-enabled NVIDIA GPUs, Apple SiliconLinux, Docker, API, CLI
Open sourceYesYes
API available-Available
SDK-Available
LLM-based--
Multimodal-Yes
AI modelLlama, Qwen, DeepSeek, Mistral, Mixtral, Phi, Gemma-
GitHub Stars33.8K80.8K
VendorAnima AI LLCvLLM Project
CategoryDeveloper ToolsDeveloper Tools
DetailsView 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

vLLM key features

  • PagedAttention memory management
  • Continuous batching
  • OpenAI-compatible API server
  • Support for various quantization
  • Distributed inference
  • Multi-hardware support