AirLLM vs DeepEval

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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DeepEval

DeepEval is an open-source unit testing framework for LLM applications.

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AttributeAirLLMDeepEval
Pricing typeFreeFree + paid (from $20/mo)
Korean supportNoPartial
PlatformsLinux, macOS, CUDA-enabled NVIDIA GPUs, Apple SiliconWeb, API, CLI
Open sourceYesYes
API available-Available
SDK-Available
LLM-based-Yes
Multimodal-Yes
AI modelLlama, Qwen, DeepSeek, Mistral, Mixtral, Phi, Gemma-
GitHub Stars33.8K18.1K
VendorAnima AI LLCConfident AI
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

DeepEval key features

  • 14+ LLM evaluation metrics
  • Pytest-based testing
  • Real-time monitoring dashboard
  • Synthetic data generator
  • Regression testing
  • CI/CD integration