diff --git a/tutorials/introduction-to-nlpmodelsjump/index.jmd b/tutorials/introduction-to-nlpmodelsjump/index.jmd
index 7053808..3939a0f 100644
--- a/tutorials/introduction-to-nlpmodelsjump/index.jmd
+++ b/tutorials/introduction-to-nlpmodelsjump/index.jmd
@@ -12,7 +12,7 @@ here only the documention specific to NLPModelsJuMP.
 
 `MathOptNLPModel` is a simple yet efficient model. It uses JuMP to define the problem,
 and can be accessed through the NLPModels API.
-An advantage of `MathOptNLPModel` over simpler models such as [`ADNLPModels`](https://github.com/JuliaSmoothOptimizers/ADNLPModels.jl) is that
+An advantage of `MathOptNLPModel` over models such as [`ADNLPModels`](https://github.com/JuliaSmoothOptimizers/ADNLPModels.jl) is that
 they provide sparse derivates.
 
 Let's define the famous Rosenbrock function