--- title: What Actually Happens Inside the Transformer MLP Layer? description: An explanation of what happens inside the MLP (feed-forward network) component of a Transformer, contrasting it with self-attention. Attention moves... canonical: https://daily.dev/posts/what-actually-happens-inside-the-transformer-mlp-layer--c1otcxcao twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: What Actually Happens Inside the Transformer MLP Layer? | daily.dev og:description: An explanation of what happens inside the MLP (feed-forward network) component of a Transformer, contrasting it with self-attention. Attention moves... og:url: https://daily.dev/posts/what-actually-happens-inside-the-transformer-mlp-layer--c1otcxcao og:image: https://api.daily.dev/og/posts/C1OTcXcaO.png og:image:alt: What Actually Happens Inside the Transformer MLP Layer? og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # What Actually Happens Inside the Transformer MLP Layer? **[Medium](https://daily.dev/sources/medium_js)** · 6 min read · 2 upvotes · 0 comments ## Summary An explanation of what happens inside the MLP (feed-forward network) component of a Transformer, contrasting it with self-attention. Attention moves information between tokens while the MLP transforms it locally through up-projection, non-linear activation, and down-projection. Walks through why non-linearity prevents stacked layers from collapsing into a single linear equation, explains modern gated MLPs like SwiGLU used in LLaMA and Mistral, and covers the key-value memory interpretation of MLPs from Geva et al.'s research. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Questions this post answers ### What does the MLP layer in a transformer do differently from the attention layer? Attention gathers relevant context across tokens in a sequence, while the MLP (feed-forward network) transforms and enriches that information locally for each token. The MLP performs up-projection to expand the vector's dimension, applies a non-linear activation to filter and create sparsity, then down-projects back into the residual stream, injecting learned value vectors for active features. _Developers building intuition for transformer internals can track deep-dive explainers like this on daily.dev._ ### Why do modern LLMs like LLaMA and Mistral use SwiGLU instead of a simple ReLU MLP? SwiGLU is a dual-path gated MLP that splits input into an up-path extracting raw content signal and a gate-path computing a dynamic control value via SiLU activation, then multiplies them element-wise. Unlike a single-path ReLU MLP's hard on/off filtering, SwiGLU acts like a volume slider, letting one branch provide content while the other continuously scales its strength. _Engineers comparing activation functions for LLM architectures can follow such breakdowns on daily.dev._ ### Why does removing the non-linear activation function break a stacked neural network? Without a non-linear activation between layers, stacking any number of linear layers mathematically collapses into a single linear equation, making depth useless. For example, two linear layers h=10x+3 and y=8h+2 combine into y=80x+26 with no activation, but inserting ReLU between them introduces a kink that prevents this collapse, since ReLU zeroing a negative value breaks proportional scaling. _Anyone reasoning through neural network design choices can find such worked proofs via daily.dev._ ## Similar posts on daily.dev - [How LLMs Actually Work](https://daily.dev/posts/how-llms-actually-work-wvseu9bao) · Lobsters · 0 upvotes · 0 comments - [Fundamentals of AI: Inside the transformer](https://daily.dev/posts/fundamentals-of-ai-inside-the-transformer-szwloqlw1) · Cisco · 0 upvotes · 0 comments --- Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#llm](https://daily.dev/tags/llm), [#deep-learning](https://daily.dev/tags/deep-learning), [#neural-networks](https://daily.dev/tags/neural-networks) [View this post on daily.dev](https://daily.dev/posts/what-actually-happens-inside-the-transformer-mlp-layer--c1otcxcao) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"What Actually Happens Inside the Transformer MLP Layer?","url":"https://daily.dev/posts/what-actually-happens-inside-the-transformer-mlp-layer--c1otcxcao","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/what-actually-happens-inside-the-transformer-mlp-layer--c1otcxcao"},"datePublished":"2026-09-04T06:49:10.009Z","dateModified":"2026-09-14T08:26:41.730Z","description":"An explanation of what happens inside the MLP (feed-forward network) component of a Transformer, contrasting it with self-attention. 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