AirLLM vs Ragas

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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Ragas

Ragas is an open-source framework for evaluating Retrieval Augmented Generation (RAG) pipelines.

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AttributeAirLLMRagas
Pricing typeFreeFree + paid
Korean supportNoNo
PlatformsLinux, macOS, CUDA-enabled NVIDIA GPUs, Apple SiliconAPI, CLI
Open sourceYesYes
API available-Available
SDK-Available
LLM-based-Yes
Multimodal--
AI modelLlama, Qwen, DeepSeek, Mistral, Mixtral, Phi, Gemma-
GitHub Stars33.8K15.6K
VendorAnima AI LLCExploding Gradients
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

Ragas key features

  • RAG-specific metrics
  • Synthetic test data generation
  • LLM-as-a-judge evaluation
  • Integration with LangChain/LlamaIndex
  • Component-wise evaluation
  • Custom metric support