For vectors or , counting measure turns the Minkowski inequality into
For , replace each displayed norm by the maximum of its coordinate absolute values. Take and . Both vectors have Lp norm one for every , but their sum has L1 norm , Euclidean norm , and L-infinity norm . Thus the same vector addition gives equality at , strict inequality at , and strict inequality at .
By contrast, and give equality for every : absolute homogeneity of a norm yields . At , the three sizes are , , and . Opposite vectors behave very differently: , so the inequality is strict whenever is nonzero. Cancellation is allowed; the bound describes the largest possible total size.
Figure 1.
Strict Minkowski inequality, equality for positive multiples, and quasi-norm failure
. Arrows show , the translated step , and their sum. Left: perpendicular unit vectors give for the Euclidean norm. Middle: and give . Right: and give for the Lq quasi-norm at . Pale curves show the corresponding unit level sets. Details.

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