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Home/Glossary/Model Quantization
AI Glossary Term

What does “Model Quantization” mean?

Definition

Reducing numeric precision of model weights to decrease memory and inference cost.

Related terms

Quantization
Converting model weights to lower precision formats such as 8-bit or 4-bit.
QLoRA
A fine-tuning technique that combines 4-bit weight quantization with LoRA adapters to reduce memory needs.
Flash Attention
An optimized attention algorithm that reduces memory use and speeds up transformer training and inference.
Memory (Agent Memory)
Stored context an AI agent uses across steps or sessions to improve continuity.
AI Agent
A software system that can observe, reason, and take actions to achieve a goal, often using tools and memory.
AI Safety
A field focused on reducing harmful behavior, failures, and misuse risks in AI systems.

Learn more in our free guides

AI Models ExplainedModel CollapseModel LifecycleModel Context Protocol

See also

Model DriftMultimodal ModelModel CardNamed Entity Recognition (NER)Mixture of Experts (MoE)Natural Language Processing (NLP)Neural NetworkMachine Learning (ML)
PreviousModel DriftNextMultimodal Model
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