# GPT-4 Has 1.8 Trillion Parameters. It Uses 2% of Them Per Token. Here Is Why That Is a Feature.

> Source: <https://pub.towardsai.net/gpt-4-has-1-8-trillion-parameters-it-uses-2-of-them-per-token-here-is-why-that-is-a-feature-5d363d3847bd?source=rss----98111c9905da---4>
> Published: 2026-07-20 06:15:30+00:00

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# GPT-4 Has 1.8 Trillion Parameters. It Uses 2% of Them Per Token. Here Is Why That Is a Feature.

The number 1.8 trillion is not the size of GPT-4. It is the size of the parameter dictionary.

When GPT-4 processes a token, it activates approximately 36 billion parameters — roughly 2% of the total.

The remaining 98% sit dormant for that specific computation.

This is not a limitation. It is an architectural choice with a precise mathematical justification, and understanding that justification changes how you think about deploying these systems at scale.

The argument is not stylistic. It is mathematical.

## The Mixture-of-Experts Architecture

GPT-4 is a Mixture-of-Experts (MoE) model. In a standard transformer feedforward block, every token passes through the same parameters.

In MoE, the feedforward layer is replaced by a set of E expert networks, and a routing function selects k of them for each token.

Formally, the MoE layer computes:

**y = Σᵢ∈Top-k(x) G(x)ᵢ · Eᵢ(x)**

Where:

- x is the input token representation

- Eᵢ(x) is the output of expert i applied to x

- G(x)ᵢ is the gating weight for expert i

- Top-k(x) is the set of k experts with highest gating scores
