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In the paper, we tackle the least squares estimators of the Vasicek-type model driven by sub-fractional Brownian motion: <disp-formula> <math display="block"> <semantics> <mrow> <mi>d</mi> <msub> <mi>X</mi> <mi>t</mi> </msub> <mo>=</mo> <mrow> <mo>(</mo> <mi>μ</mi> <mo>+</mo> <mi>θ</mi> <msub> <mi>X</mi> <mi>t</mi> </msub> <mo>)</mo> </mrow> <mi>d</mi> <mi>t</mi> <mo>+</mo> <mi>d</mi> <msubsup> <mi>S</mi> <mi>t</mi> <mi>H</mi> </msubsup> <mo>,</mo> <mspace width="1.em"></mspace> <mi>t</mi> <mo>≥</mo> <mn>0</mn> </mrow> </semantics> </math> </disp-formula> with <inline-formula> <math display="inline"> <semantics> <mrow> <msub> <mi>X</mi> <mn>0</mn> </msub> <mo>=</mo> <mn>0</mn> </mrow> </semantics> </math> </inline-formula>, where <inline-formula> <math display="inline"> <semantics> <msup> <mi>S</mi> <mi>H</mi> </msup> </semantics> </math> </inline-formula> is a sub-fractional Brownian motion whose Hurst index <i>H</i> is greater than <inline-formula> <math display="inline"> <semantics> <mfrac> <mn>1</mn> <mn>2</mn> </mfrac> </semantics> </math> </inline-formula>, and <inline-formula> <math display="inline"> <semantics> <mrow> <mi>μ</mi> <mo>∈</mo> <mi mathvariant="double-struck">R</mi> </mrow> </semantics> </math> </inline-formula>, <inline-formula> <math display="inline"> <semantics> <mrow> <mi>θ</mi> <mo>∈</mo> <msup> <mi mathvariant="double-struck">R</mi> <mo>+</mo> </msup> </mrow> </semantics> </math> </inline-formula> are two unknown parameters. Based on the so-called continuous observations, we suggest the least square estimators of <inline-formula> <math display="inline"> <semantics> <mi>μ</mi> </semantics> </math> </inline-formula> and <inline-formula> <math display="inline"> <semantics> <mi>θ</mi> </semantics> </math> </inline-formula> and discuss the consistency and asymptotic distributions of the two estimators.