AI2026-05-17
Dense Model
Also known as: Dense Model / Dense Transformer / 高密度モデル
A standard Transformer model where all parameters participate in processing every token, as opposed to MoE's sparse expert selection. Compute scales proportionally with parameter count.
Overview
A Dense Model is a standard Transformer where every parameter activates for every input token. Llama, Qwen Dense, Gemma, and Phi are examples. The term is used in contrast to MoE: compute scales linearly with parameter count, so scaling up requires proportionally more compute.
When to choose Dense vs MoE
Dense models require less VRAM than MoE at the same parameter count and are simpler to deploy. 7B-27B dense models run efficiently on consumer GPUs and are the dominant choice for local LLM use cases.
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