Quantization
Also known as: Model Quantization, Weight Quantization
In one sentence
A compression technique that reduces AI model size and memory usage by using lower-precision numbers, making models faster and cheaper to run.
Explain like I'm 12
Like compressing a huge photo file to make it smaller—you lose a tiny bit of quality, but now it loads way faster and takes up less space.
In context
Converting a 70B model from 32-bit to 8-bit or 4-bit precision can reduce size from 140GB to 35GB or less, enabling local deployment on consumer hardware.
See also
Related Guides
Learn more about Quantization in these guides:
Quantization and Distillation Deep Dive
AdvancedMaster advanced model compression: quantization-aware training, mixed precision, and distillation strategies for production deployment.
8 min readModel Compression: Smaller, Faster AI
AdvancedCompress AI models with quantization, pruning, and distillation. Deploy faster, cheaper models without sacrificing much accuracy.
7 min readDeployment Patterns: Serverless, Edge, and Containers
IntermediateHow to deploy AI systems in production. Compare serverless, edge, container, and self-hosted options.
13 min read