AirLLM vs Groq

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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Groq

Groq provides an inference platform using custom LPU chips designed for high speed and low cost.

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AttributeAirLLMGroq
Pricing typeFreeFree + paid (from $0/mo)
Korean supportNoPartial
PlatformsLinux, macOS, CUDA-enabled NVIDIA GPUs, Apple SiliconWeb, CLI, API
Open sourceYesNo
API available-Available
SDK-Available
LLM-based-Yes
Multimodal-Yes
AI modelLlama, Qwen, DeepSeek, Mistral, Mixtral, Phi, GemmaGPT, Whisper, Groq Compound, Groq Compound Mini, Qwen3.6, MiniMax M2.7, Orpheus V1 English, Orpheus Arabic Saudi, Llama
GitHub Stars33.8K-
VendorAnima AI LLCGroq
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

Groq key features

  • Custom LPU inference chips
  • Low-latency, high-speed model execution
  • OpenAI-compatible API integration
  • GroqCloud management console