---
title: "Basic Dimensioning"
slug: "basic-dimensioning"
updated: 2026-05-29T16:03:21Z
published: 2026-05-29T16:03:21Z
canonical: "kb.capvidia.com/basic-dimensioning"
---

> ## Documentation Index
> Fetch the complete documentation index at: https://kb.capvidia.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Basic Dimensioning

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Basic dimensions define perfect geometry. Basic dimensions may be used to define the perfect form and size of individual features, and they may be used to define perfect geometric relationships, such as the perfect orientation and location between features. Basic dimensions are also used to define datum targets and the extents of specifications, such as between (e.g. A↔B) and limited areas on parts. A rectangular frame is placed around a basic dimension value. Basic dimensions may be explicitly defined (displayed) on a drawing or an annotated model and basic dimensions may be implicitly defined, such as by stating that all dimensional values obtained from a 3D CAD model are basic. Remember, basic 90° angular dimensions do not need to be displayed on drawings because of the fundamental rules in ASME Y14.5.

The arrangement of basic dimensions is less important than the arrangement of directly-toleranced dimensions (+/-). Arranging directly-toleranced dimensions differently changes tolerance requirements, because directly-toleranced dimensions include tolerances. Arranging basic dimensions differently does not change tolerance requirements, because basic dimensions define perfect geometry – basic dimensions do not include a tolerance. Thus, the dimensioning methods shown in the following figure are equivalent.

![Picture](data:image/png;base64,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)

Figure 1 – Two Ways to Dimension Relationships Between Features