diff --git a/docs/Project.toml b/docs/Project.toml
index 1e7c869d..9cfe5269 100644
--- a/docs/Project.toml
+++ b/docs/Project.toml
@@ -19,7 +19,7 @@ InfiniteOpt = "0.5"
 Ipopt = "1.6"
 HiGHS = "1"
 julia = "1.6"
-JuMP = "1.22"
+JuMP = "1.23"
 Literate = "2.18"
 Plots = "1"
 SpecialFunctions = "2"
diff --git a/docs/src/guide/measure.md b/docs/src/guide/measure.md
index 36b22365..fac3eeca 100644
--- a/docs/src/guide/measure.md
+++ b/docs/src/guide/measure.md
@@ -342,12 +342,12 @@ tmodel = transformation_model(model);
 
 # output
 A JuMP Model
-Minimization problem with:
-Variables: 3
-Objective function type: QuadExpr
-Model mode: AUTOMATIC
-CachingOptimizer state: NO_OPTIMIZER
-Solver name: No optimizer attached.
+├ solver: none
+├ objective_sense: MIN_SENSE
+│ └ objective_function_type: QuadExpr
+├ num_variables: 3
+├ num_constraints: 0
+└ Names registered in the model: none
 
 ```
 
@@ -384,12 +384,12 @@ trans_m = transformation_model(model);
 
 # output
 A JuMP Model
-Minimization problem with:
-Variables: 5
-Objective function type: QuadExpr
-Model mode: AUTOMATIC
-CachingOptimizer state: NO_OPTIMIZER
-Solver name: No optimizer attached.
+├ solver: none
+├ objective_sense: MIN_SENSE
+│ └ objective_function_type: QuadExpr
+├ num_variables: 5
+├ num_constraints: 0
+└ Names registered in the model: none
 
 ```
 Now let's look again at the number of supports, the transcription of `u`, and the 
@@ -442,12 +442,12 @@ tmodel = transformation_model(model);
 
 # output
 A JuMP Model
-Minimization problem with:
-Variables: 2
-Objective function type: QuadExpr
-Model mode: AUTOMATIC
-CachingOptimizer state: NO_OPTIMIZER
-Solver name: No optimizer attached.
+├ solver: none
+├ objective_sense: MIN_SENSE
+│ └ objective_function_type: QuadExpr
+├ num_variables: 2
+├ num_constraints: 0
+└ Names registered in the model: none
 
 ```
 Then we get the supports are consistent for `u` and the integral:
diff --git a/docs/src/guide/model.md b/docs/src/guide/model.md
index 56217af1..42acb990 100644
--- a/docs/src/guide/model.md
+++ b/docs/src/guide/model.md
@@ -32,7 +32,7 @@ Feasibility problem with:
   Measures: 0
 Transformation backend information:
   Backend type: TranscriptionBackend
-  Solver name: No optimizer attached.
+  Solver: none
   Transformation built and up-to-date: false
 ```
 Ultimately, `model` will be solved via a transformation backend. By default, 
@@ -52,7 +52,7 @@ Feasibility problem with:
   Measures: 0
 Transformation backend information:
   Backend type: TranscriptionBackend
-  Solver name: No optimizer attached.
+  Solver: none
   Transformation built and up-to-date: false
 ```
 
@@ -72,7 +72,7 @@ Feasibility problem with:
   Measures: 0
 Transformation backend information:
   Backend type: TranscriptionBackend
-  Solver name: Ipopt
+  Solver: Ipopt
   Transformation built and up-to-date: false
 ```
 For completeness, the table of currently supported JuMP compatible optimizers 
@@ -96,7 +96,7 @@ Feasibility problem with:
   Measures: 0
 Transformation backend information:
   Backend type: TranscriptionBackend
-  Solver name: Ipopt
+  Solver: Ipopt
   Transformation built and up-to-date: false
 ```
 
@@ -120,11 +120,11 @@ julia> using InfiniteOpt, Ipopt
 julia> backend = TranscriptionBackend(Ipopt.Optimizer)
 A TranscriptionBackend that uses a
 A JuMP Model
-Feasibility problem with:
-Variables: 0
-Model mode: AUTOMATIC
-CachingOptimizer state: EMPTY_OPTIMIZER
-Solver name: Ipopt
+├ solver: Ipopt
+├ objective_sense: FEASIBILITY_SENSE
+├ num_variables: 0
+├ num_constraints: 0
+└ Names registered in the model: none
 ```
 
 We query the underlying transformation backend, transformation model, and transformation
@@ -137,19 +137,19 @@ julia> using InfiniteOpt; model = InfiniteModel();
 julia> tbackend = transformation_backend(model)
 A TranscriptionBackend that uses a
 A JuMP Model
-Feasibility problem with:
-Variables: 0
-Model mode: AUTOMATIC
-CachingOptimizer state: NO_OPTIMIZER
-Solver name: No optimizer attached.
+├ solver: none
+├ objective_sense: FEASIBILITY_SENSE
+├ num_variables: 0
+├ num_constraints: 0
+└ Names registered in the model: none
 
 julia> tmodel = transformation_model(model)
 A JuMP Model
-Feasibility problem with:
-Variables: 0
-Model mode: AUTOMATIC
-CachingOptimizer state: NO_OPTIMIZER
-Solver name: No optimizer attached.
+├ solver: none
+├ objective_sense: FEASIBILITY_SENSE
+├ num_variables: 0
+├ num_constraints: 0
+└ Names registered in the model: none
 
 julia> data = transformation_data(model);
 ```
@@ -163,11 +163,11 @@ julia> set_transformation_backend(model, TranscriptionBackend(Ipopt.Optimizer))
 julia> tbackend = transformation_backend(model)
 A TranscriptionBackend that uses a
 A JuMP Model
-Feasibility problem with:
-Variables: 0
-Model mode: AUTOMATIC
-CachingOptimizer state: EMPTY_OPTIMIZER
-Solver name: Ipopt
+├ solver: Ipopt
+├ objective_sense: FEASIBILITY_SENSE
+├ num_variables: 0
+├ num_constraints: 0
+└ Names registered in the model: none
 ```
 Again, since `TranscriptionBackend` is the default, the following models are equivalent:
 ```jldoctest
@@ -187,7 +187,7 @@ Feasibility problem with:
   Measures: 0
 Transformation backend information:
   Backend type: TranscriptionBackend
-  Solver name: Ipopt
+  Solver: Ipopt
   Transformation built and up-to-date: false
 ```
 
diff --git a/docs/src/guide/optimize.md b/docs/src/guide/optimize.md
index 39324924..da3167cc 100644
--- a/docs/src/guide/optimize.md
+++ b/docs/src/guide/optimize.md
@@ -97,27 +97,27 @@ let's extract the transformation backend from the example above in the basic usa
 julia> backend = transformation_backend(model)
 A TranscriptionBackend that uses a
 A JuMP Model
-Minimization problem with:
-Variables: 11
-Objective function type: AffExpr
-`AffExpr`-in-`MathOptInterface.EqualTo{Float64}`: 1 constraint
-`AffExpr`-in-`MathOptInterface.GreaterThan{Float64}`: 10 constraints
-`VariableRef`-in-`MathOptInterface.GreaterThan{Float64}`: 11 constraints
-Model mode: AUTOMATIC
-CachingOptimizer state: ATTACHED_OPTIMIZER
-Solver name: Ipopt
+├ solver: Ipopt
+├ objective_sense: MIN_SENSE
+│ └ objective_function_type: AffExpr
+├ num_variables: 11
+├ num_constraints: 22
+│ ├ AffExpr in MOI.EqualTo{Float64}: 1
+│ ├ AffExpr in MOI.GreaterThan{Float64}: 10
+│ └ VariableRef in MOI.GreaterThan{Float64}: 11
+└ Names registered in the model: none
 
 julia> tmodel = transformation_model(model)
 A JuMP Model
-Minimization problem with:
-Variables: 11
-Objective function type: AffExpr
-`AffExpr`-in-`MathOptInterface.EqualTo{Float64}`: 1 constraint
-`AffExpr`-in-`MathOptInterface.GreaterThan{Float64}`: 10 constraints
-`VariableRef`-in-`MathOptInterface.GreaterThan{Float64}`: 11 constraints
-Model mode: AUTOMATIC
-CachingOptimizer state: ATTACHED_OPTIMIZER
-Solver name: Ipopt
+├ solver: Ipopt
+├ objective_sense: MIN_SENSE
+│ └ objective_function_type: AffExpr
+├ num_variables: 11
+├ num_constraints: 22
+│ ├ AffExpr in MOI.EqualTo{Float64}: 1
+│ ├ AffExpr in MOI.GreaterThan{Float64}: 10
+│ └ VariableRef in MOI.GreaterThan{Float64}: 11
+└ Names registered in the model: none
 ```
 
 The `JuMP` variable(s) stored in the transformation backend that correspond to a 
diff --git a/docs/src/guide/transcribe.md b/docs/src/guide/transcribe.md
index 51793e2a..71e33871 100644
--- a/docs/src/guide/transcribe.md
+++ b/docs/src/guide/transcribe.md
@@ -68,16 +68,16 @@ julia> build_transformation_backend!(inf_model)
 
 julia> trans_model = transformation_model(inf_model)
 A JuMP Model
-Minimization problem with:
-Variables: 4
-Objective function type: AffExpr
-`AffExpr`-in-`MathOptInterface.EqualTo{Float64}`: 1 constraint
-`QuadExpr`-in-`MathOptInterface.LessThan{Float64}`: 3 constraints
-`VariableRef`-in-`MathOptInterface.GreaterThan{Float64}`: 3 constraints
-`VariableRef`-in-`MathOptInterface.ZeroOne`: 1 constraint
-Model mode: AUTOMATIC
-CachingOptimizer state: NO_OPTIMIZER
-Solver name: No optimizer attached.
+├ solver: none
+├ objective_sense: MIN_SENSE
+│ └ objective_function_type: AffExpr
+├ num_variables: 4
+├ num_constraints: 8
+│ ├ AffExpr in MOI.EqualTo{Float64}: 1
+│ ├ QuadExpr in MOI.LessThan{Float64}: 3
+│ ├ VariableRef in MOI.GreaterThan{Float64}: 3
+│ └ VariableRef in MOI.ZeroOne: 1
+└ Names registered in the model: none
 
 julia> print(trans_model)
 Min 2 z + y(0.0) + y(5.0) + y(10.0)
@@ -357,27 +357,27 @@ which wraps [`build_transcription_backend!`](@ref InfiniteOpt.TranscriptionOpt.b
 julia> backend1 = TranscriptionBackend() # make an empty backend
 A TranscriptionBackend that uses a
 A JuMP Model
-Feasibility problem with:
-Variables: 0
-Model mode: AUTOMATIC
-CachingOptimizer state: NO_OPTIMIZER
-Solver name: No optimizer attached.
+├ solver: none
+├ objective_sense: FEASIBILITY_SENSE
+├ num_variables: 0
+├ num_constraints: 0
+└ Names registered in the model: none
 
 julia> build_transformation_backend!(inf_model); 
 
 julia> backend2 = transformation_backend(inf_model) # generate from an InfiniteModel
 A TranscriptionBackend that uses a
 A JuMP Model
-Minimization problem with:
-Variables: 4
-Objective function type: AffExpr
-`AffExpr`-in-`MathOptInterface.EqualTo{Float64}`: 1 constraint
-`QuadExpr`-in-`MathOptInterface.LessThan{Float64}`: 3 constraints
-`VariableRef`-in-`MathOptInterface.GreaterThan{Float64}`: 3 constraints
-`VariableRef`-in-`MathOptInterface.ZeroOne`: 1 constraint
-Model mode: AUTOMATIC
-CachingOptimizer state: NO_OPTIMIZER
-Solver name: No optimizer attached.
+├ solver: none
+├ objective_sense: MIN_SENSE
+│ └ objective_function_type: AffExpr
+├ num_variables: 4
+├ num_constraints: 8
+│ ├ AffExpr in MOI.EqualTo{Float64}: 1
+│ ├ QuadExpr in MOI.LessThan{Float64}: 3
+│ ├ VariableRef in MOI.GreaterThan{Float64}: 3
+│ └ VariableRef in MOI.ZeroOne: 1
+└ Names registered in the model: none
 ```
 The call to `build_transformation_backend!` is the backbone 
 behind infinite model transformation and is what encapsulates all the methods to 
@@ -391,11 +391,11 @@ via [`transformation_model`](@ref):
 ```jldoctest transcribe; setup = :(empty!(inf_model.backend))
 julia> transformation_model(inf_model)
 A JuMP Model
-Feasibility problem with:
-Variables: 0
-Model mode: AUTOMATIC
-CachingOptimizer state: NO_OPTIMIZER
-Solver name: No optimizer attached.
+├ solver: none
+├ objective_sense: FEASIBILITY_SENSE
+├ num_variables: 0
+├ num_constraints: 0
+└ Names registered in the model: none
 ```
 Here we observe that such a model is currently empty and hasn't been populated 
 yet.
diff --git a/docs/src/tutorials/quick_start.md b/docs/src/tutorials/quick_start.md
index 1314ab8b..98ce0777 100644
--- a/docs/src/tutorials/quick_start.md
+++ b/docs/src/tutorials/quick_start.md
@@ -72,7 +72,7 @@ Feasibility problem with:
   Measures: 0
 Transformation backend information:
   Backend type: TranscriptionBackend
-  Solver name: Ipopt
+  Solver: Ipopt
   Transformation built and up-to-date: false
 ```
 Learn more about `InfiniteModel`s and optimizers on our 
diff --git a/src/TranscriptionOpt/model.jl b/src/TranscriptionOpt/model.jl
index 49d6581a..a6441656 100644
--- a/src/TranscriptionOpt/model.jl
+++ b/src/TranscriptionOpt/model.jl
@@ -130,6 +130,20 @@ function TranscriptionBackend(optimizer_constructor; kwargs...)
     return InfiniteOpt.JuMPBackend{Transcription}(model, TranscriptionData())
 end
 
+# Get the solver name from MOI
+# Inspired by https://github.com/jump-dev/JuMP.jl/blob/ce946b7092c45bdac916c9b531a13a5b929d45f0/src/print.jl#L281-L291
+function _try_solver_name(model)
+    if mode(model) != JuMP.DIRECT &&
+       MOI.Utilities.state(backend(model)) == MOI.Utilities.NO_OPTIMIZER
+        return "none"
+    end
+    try
+        return MOI.get(backend(model), MOI.SolverName())
+    catch
+        return "unknown"
+    end
+end
+
 # Printing
 function JuMP.show_backend_summary(
     io::IO,
@@ -148,9 +162,7 @@ function JuMP.show_backend_summary(
         # TODO add approximation method info (requires InfiniteOpt refactoring)
     end
     # solver name
-    moi_summary = sprint(JuMP.show_backend_summary, backend.model)
-    solver_str = filter(startswith("Solver"), split(moi_summary, "\n"))[1]
-    println(io, "  ", solver_str)
+    println(io, "  Solver: ", _try_solver_name(backend.model))
     return
 end
 
diff --git a/src/backends.jl b/src/backends.jl
index e660f0e8..7ec0524d 100644
--- a/src/backends.jl
+++ b/src/backends.jl
@@ -55,11 +55,11 @@ Return the underlying model used by the transformation backend.
 ```julia-repl
 julia> trans_model = transformation_model(model)
 A JuMP Model
-Feasibility problem with:
-Variables: 0
-Model mode: AUTOMATIC
-CachingOptimizer state: NO_OPTIMIZER
-Solver name: No optimizer attached.
+├ solver: none
+├ objective_sense: FEASIBILITY_SENSE
+├ num_variables: 0
+├ num_constraints: 0
+└ Names registered in the model: none
 ```
 """
 transformation_model(model::InfiniteModel) = transformation_model(model.backend)
@@ -106,22 +106,22 @@ will be removed.
 julia> transformation_backend(model)
 A TranscriptionBackend that uses a
 A JuMP Model
-Feasibility problem with:
-Variables: 0
-Model mode: AUTOMATIC
-CachingOptimizer state: NO_OPTIMIZER
-Solver name: No optimizer attached.
+├ solver: none
+├ objective_sense: FEASIBILITY_SENSE
+├ num_variables: 0
+├ num_constraints: 0
+└ Names registered in the model: none
 
 julia> set_transformation_backend(model, TranscriptionBackend(Ipopt.Optimizer))
 
 julia> transformation_backend(model)
 A TranscriptionBackend that uses a
 A JuMP Model
-Feasibility problem with:
-Variables: 0
-Model mode: AUTOMATIC
-CachingOptimizer state: EMPTY_OPTIMIZER
-Solver name: Ipopt
+├ solver: Ipopt
+├ objective_sense: FEASIBILITY_SENSE
+├ num_variables: 0
+├ num_constraints: 0
+└ Names registered in the model: none
 ```
 """
 function set_transformation_backend(
@@ -145,11 +145,11 @@ Retrieve the transformation backend used by the `model`.
 julia> transformation_backend(model)
 A TranscriptionBackend that uses a
 A JuMP Model
-Feasibility problem with:
-Variables: 0
-Model mode: AUTOMATIC
-CachingOptimizer state: NO_OPTIMIZER
-Solver name: No optimizer attached.
+├ solver: none
+├ objective_sense: FEASIBILITY_SENSE
+├ num_variables: 0
+├ num_constraints: 0
+└ Names registered in the model: none
 ```
 """
 function transformation_backend(model::InfiniteModel)
@@ -664,11 +664,11 @@ julia> set_optimizer(model, HiGHS.Optimizer)
 
 julia> transformation_model(model)
 A JuMP Model
-Feasibility problem with:
-Variables: 0
-Model mode: AUTOMATIC
-CachingOptimizer state: EMPTY_OPTIMIZER
-Solver name: HiGHS
+├ solver: HiGHS
+├ objective_sense: FEASIBILITY_SENSE
+├ num_variables: 0
+├ num_constraints: 0
+└ Names registered in the model: none
 ```
 """
 function JuMP.set_optimizer(
diff --git a/src/constraints.jl b/src/constraints.jl
index 8efc96f7..ebe777c4 100644
--- a/src/constraints.jl
+++ b/src/constraints.jl
@@ -11,18 +11,21 @@ Extend `JuMP.owner_model` to return the infinite model associated with `cref`.
 julia> model = owner_model(cref)
 An InfiniteOpt Model
 Minimization problem with:
-Finite Parameters: 0
-Infinite Parameters: 3
-Variables: 3
-Derivatives: 0
-Measures: 0
-Objective function type: GeneralVariableRef
-`GenericAffExpr{Float64,GeneralVariableRef}`-in-`MathOptInterface.EqualTo{Float64}`: 1 constraint
-Names registered in the model: g, t, h, x
-Optimizer model backend information:
-Model mode: AUTOMATIC
-CachingOptimizer state: NO_OPTIMIZER
-Solver name: No optimizer attached.
+  Finite parameters: 0
+  Infinite parameter: 1
+  Variables: 3
+  Derivatives: 0
+  Measures: 0
+  Objective function type: GenericAffExpr{Float64, GeneralVariableRef}
+  `GenericAffExpr{Float64, GeneralVariableRef}`-in-`MathOptInterface.GreaterThan{Float64}`: 1 constraint
+  `GenericAffExpr{Float64, GeneralVariableRef}`-in-`MathOptInterface.EqualTo{Float64}`: 1 constraint
+  `GeneralVariableRef`-in-`MathOptInterface.GreaterThan{Float64}`: 3 constraints
+Names registered in the model: c1, c2, t, y, z
+Transformation backend information:
+  Backend type: TranscriptionBackend
+  `t` transcribed over 10 supports
+  Solver: Ipopt
+  Transformation built and up-to-date: true
 ```
 """
 JuMP.owner_model(cref::InfOptConstraintRef) = cref.model
diff --git a/src/datatypes.jl b/src/datatypes.jl
index 3ccc6b6c..7eaef9eb 100644
--- a/src/datatypes.jl
+++ b/src/datatypes.jl
@@ -1430,7 +1430,7 @@ Feasibility problem with:
   Measures: 0
 Transformation backend information:
   Backend type: TranscriptionBackend
-  Solver name: No optimizer attached.
+  Solver: none
   Transformation built and up-to-date: false
 
 julia> model = InfiniteModel(Ipopt.Optimizer)
@@ -1443,7 +1443,7 @@ Feasibility problem with:
   Measures: 0
 Transformation backend information:
   Backend type: TranscriptionBackend
-  Solver name: Ipopt
+  Solver: Ipopt
   Transformation built and up-to-date: false
 ```
 """
diff --git a/src/general_variables.jl b/src/general_variables.jl
index 8076c477..c926fea5 100644
--- a/src/general_variables.jl
+++ b/src/general_variables.jl
@@ -81,19 +81,22 @@ Extend `JuMP.owner_model` to return the model where `vref` is stored.
 ```julia-repl
 julia> owner_model(vref)
 An InfiniteOpt Model
-Feasibility problem with:
-Finite Parameters: 0
-Infinite Parameters: 0
-Variable: 1
-Derivatives: 0
-Measures: 0
-`FiniteVariableRef`-in-`MathOptInterface.GreaterThan{Float64}`: 1 constraint
-`FiniteVariableRef`-in-`MathOptInterface.LessThan{Float64}`: 1 constraint
-Names registered in the model: vref
-Optimizer model backend information:
-Model mode: AUTOMATIC
-CachingOptimizer state: NO_OPTIMIZER
-Solver name: No optimizer attached.
+Minimization problem with:
+  Finite parameters: 0
+  Infinite parameter: 1
+  Variables: 3
+  Derivatives: 0
+  Measures: 0
+  Objective function type: GenericAffExpr{Float64, GeneralVariableRef}
+  `GenericAffExpr{Float64, GeneralVariableRef}`-in-`MathOptInterface.GreaterThan{Float64}`: 1 constraint
+  `GenericAffExpr{Float64, GeneralVariableRef}`-in-`MathOptInterface.EqualTo{Float64}`: 1 constraint
+  `GeneralVariableRef`-in-`MathOptInterface.GreaterThan{Float64}`: 3 constraints
+Names registered in the model: c1, c2, t, y, z
+Transformation backend information:
+  Backend type: TranscriptionBackend
+  `t` transcribed over 10 supports
+  Solver: Ipopt
+  Transformation built and up-to-date: true
 ```
 """
 function JuMP.owner_model(vref::GeneralVariableRef)::InfiniteModel
diff --git a/test/TranscriptionOpt/model.jl b/test/TranscriptionOpt/model.jl
index 40f85f2c..9ab47d73 100644
--- a/test/TranscriptionOpt/model.jl
+++ b/test/TranscriptionOpt/model.jl
@@ -23,7 +23,15 @@ end
     # test JuMP.show_backend_summary
     @testset "JuMP.show_backend_summary" begin
         expected = "  Backend type: TranscriptionBackend\n  `t` transcribed over 4 supports\n  " *
-                   "`x` transcribed over 5 supports\n  Solver name: No optimizer attached.\n"
+                   "`x` transcribed over 5 supports\n  Solver: none.\n"
+        @test sprint(show_backend_summary, m, tb) == expected
+        set_optimizer(tb.model, () -> MOIU.MockOptimizer(MOIU.Model{Float64}()))
+        expected = "  Backend type: TranscriptionBackend\n  `t` transcribed over 4 supports\n  " *
+                   "`x` transcribed over 5 supports\n  Solver: Mock.\n"
+        @test sprint(show_backend_summary, m, tb) == expected
+        set_optimizer(tb.model, () -> MOIU.Model{Float64}())
+        expected = "  Backend type: TranscriptionBackend\n  `t` transcribed over 4 supports\n  " *
+                   "`x` transcribed over 5 supports\n  Solver: unknown.\n"
         @test sprint(show_backend_summary, m, tb) == expected
     end
     # test show