---
title: "Discussion on \"Why output tokens cost more than input tokens and what that means for feature design\" | Hashnode"
description: "Discussion on \"Why output tokens cost more than input tokens and what that means for feature design\". There's a pricing detail most product teams don't look at closely enough.\nInput tokens and output tokens are not the same price. Output tokens cost more. Sometimes 2-3x more depending on the model. Th"
url: "https://hashnode.com/posts/why-output-tokens-cost-more-than-input-tokens-and-what-that-means-for-feature-design/6a61b21193269086fdb4bea2"
---

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# [Why output tokens cost more than input tokens and what that means for feature design](https://leveragepoints.io/why-output-tokens-cost-more-than-input-tokens-and-what-that-means-for-feature-design?utm_source=hashnode&utm_medium=feed)

There's a pricing detail most product teams don't look at closely enough. Input tokens and output tokens are not the same price. Output tokens cost more. Sometimes 2-3x more depending on the model. Th

Jul 23 · 4 min read · leveragepoints.io  
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## Written by

[Abdulwaheed A A](https://hashnode.com/@habiz)

@habiz

  
[View profile](https://hashnode.com/@habiz)

Building Products

I lead the strategy and delivery of products and systems that solve real problems, support commercial goals and scale across teams and markets. My work spans platform foundations, user-facing experiences, commercial tools and developer products, and I adapt my approach to the needs of each domain. My experience covers early-stage, scale-up and enterprise product environments, combining hands-on delivery with team leadership and award-winning work recognised across several innovative organisations.

## Responses 2

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[Mateo Ruiz](https://hashnode.com/@mateoruiz)

[Jul 23](https://hashnode.com/posts/why-output-tokens-cost-more-than-input-tokens-and-what-that-means-for-feature-design/6a61b21193269086fdb4bea2/comment/6a61d4d56d6cb2f58582c4a1)

This is a point more product teams should quantify early. We often optimize prompts for quality but forget that response length is a product decision with a direct impact on unit economics.

One pattern that's worked well is designing for progressive disclosure: give the concise answer first, then let users expand for more detail only when they need it. It improves UX while avoiding unnecessary output tokens on every request.

The same thinking also makes model routing more effective. If a feature consistently needs long-form generation, reducing output length by even 15–20% can have a bigger cost impact than shaving a few input tokens, especially as usage scales.

[Abdulwaheed A A](https://hashnode.com/@habiz)

[Aug 3](https://hashnode.com/posts/why-output-tokens-cost-more-than-input-tokens-and-what-that-means-for-feature-design/6a61b21193269086fdb4bea2/comment/6a61d4d56d6cb2f58582c4a1#reply-6a705b03d8a2070e5612845d)

This is actually an interesting perspective in re-using existing UX patterns users are familiar with to avoid unnecessary output tokens and efficient model routing. More like let user request for long-form when needed