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Distance Between Two Points Calculator (2D / 3D)

Enter two points P = (x₁, y₁[, z₁]) and Q = (x₂, y₂[, z₂]). The tool applies the Euclidean distance formula d = √Σ(qᵢ − pᵢ)², then reports each axis delta Δᵢ, the midpoint M = ((p + q) / 2) and the Manhattan / Chebyshev distances. Coordinate-geometry homework, CAD anchor-point measurements, distance checks in game development and feature-vector spacing in machine learning all rely on the same formula.

Point P (start)
Point Q (end)

Euclidean distance d

5

d = √((4−1)² + (6−2)²) = 5

Midpoint M

(2.5, 4)

Δx = qₓ − pₓ

3

Δy = qᵧ − pᵧ

4

Manhattan distance (Σ|Δ|)

7

Chebyshev distance (max|Δ|)

4

Euclidean distance d = √(Δx² + Δy²) is the straight-line gap between the two points. The Manhattan (city-block) and Chebyshev (king-move) distances are reported as well, so you can pick the right metric for your problem.

Formula

2D: d = √((x₂ − x₁)² + (y₂ − y₁)²) 3D: d = √((x₂ − x₁)² + (y₂ − y₁)² + (z₂ − z₁)²) Midpoint: M = ((x₁ + x₂) / 2, (y₁ + y₂) / 2 [, (z₁ + z₂) / 2]) Manhattan d₁ = Σ|qᵢ − pᵢ| Chebyshev d∞ = max|qᵢ − pᵢ|

Frequently asked

When should I use Euclidean distance, and when Manhattan distance?

Use Euclidean distance when motion is free in any direction — geometry problems, CAD work, 3D graphics, radar range. Use Manhattan distance when motion is constrained to axis-aligned moves — chessboard taxicab paths, downtown street navigation, PCB trace routing. In machine learning, k-NN and k-means default to Euclidean distance; high-dimensional sparse features (e.g. bag-of-words text) typically switch to cosine similarity instead. Chebyshev distance is the "king-move" distance (max|Δ|), useful for chessboards and warehouse-robot move counting.

Can I use this calculator with latitude/longitude coordinates?

No (unless the area is small enough — under ~1 km — for a rough approximation). The Earth is a sphere, and treating one degree of latitude/longitude as ~111 km only works near the equator; the error grows quickly at higher latitudes. For geographic distance use the haversine formula (or the more precise Vincenty formula on an ellipsoid model) — the site's Haversine calculator takes two lat/long pairs directly. Euclidean distance is correct for planar Cartesian coordinates such as projected map x/y, UTM coordinates or CAD coordinates.

How are the midpoint formula and the distance formula related?

Both formulas describe the same pair of points P, Q. The distance formula answers "how far apart are they?", and the midpoint formula answers "where is the centre of the segment?" The midpoint is the component-wise average: M = ((x₁ + x₂) / 2, (y₁ + y₂) / 2[, (z₁ + z₂) / 2]). A useful identity: the distances from M to P and from M to Q are equal, and each equals d(P, Q) / 2. The midpoint formula shows up in perpendicular-bisector proofs, in finding circle centres from two points, and as the linear interpolation lerp(P, Q, 0.5) used in graphics and animation.

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