LMDeploy vs AirLLM

A side-by-side comparison of features, pricing, and characteristics.

LMDeploy

LMDeploy is an efficient toolkit for compressing, deploying, and serving LLMs.

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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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AttributeLMDeployAirLLM
Pricing typeFreeFree
Korean supportYesNo
PlatformsLinux, API, CLILinux, macOS, CUDA-enabled NVIDIA GPUs, Apple Silicon
Open sourceYesYes
API availableAvailable-
SDKAvailable-
LLM-basedYes-
MultimodalYes-
AI model-Llama, Qwen, DeepSeek, Mistral, Mixtral, Phi, Gemma
GitHub Stars7.9K33.8K
VendorShanghai AI Lab (InternLM Team)Anima AI LLC
CategoryDeveloper ToolsDeveloper Tools
DetailsView View

LMDeploy key features

  • TurboMind Inference Engine
  • AWQ 4-bit Quantization
  • Continuous Batching
  • KV Cache Management
  • Multi-GPU Distributed Inference
  • OpenAI-compatible API

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