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Attention
A mechanism that lets a neural network weigh the relevance of different positions when computing a representation.
Context Window
The amount of tokenized input and generated text a model can consider within one inference context.
GPU
A highly parallel processor widely used to train and run modern machine-learning models.
Inference
The process of running a trained model on new input to produce predictions, embeddings, or generated output.
KV Cache
A cache of attention keys and values used to avoid recomputing earlier context during autoregressive generation.
Latency and Throughput
Two core serving metrics describing response delay and the amount of work a system completes over time.
Mistral AI
An AI company providing models and inference services, with a guide to model-specific licenses, hosted versus self-operated deployment and task-level comparison.
Mixture of Experts (MoE)
A model architecture that routes each input to a subset of specialized parameter blocks called experts.
Quantization
A technique that represents model weights or activations with lower numerical precision to reduce resource use.
Transformer
A neural network architecture that processes sequences primarily through attention mechanisms.