diff --git a/src/backend/mxnet/model.jl b/src/backend/mxnet/model.jl
index 36b870f8..4c2f08de 100644
--- a/src/backend/mxnet/model.jl
+++ b/src/backend/mxnet/model.jl
@@ -1,5 +1,5 @@
 
-type MXModel <: Model
+type Model <: Flux.Model
   model::Any
   params::Dict{Symbol,Any}
   grads::Dict{Symbol,Any}
@@ -25,18 +25,18 @@ function mxgrads(mxargs)
   end
 end
 
-function loadparams!(model::MXModel)
+function loadparams!(model::Model)
   for (name, arr) in model.exec.arg_dict
     haskey(model.params, name) && copy!(arr, model.params[name])
   end
   return model
 end
 
-function mxnet(model::Model, input)
+function mxnet(model::Flux.Model, input)
   params, stacks, node = tograph(model, mx.Variable(:input))
   args = merge(mxargs(params), Dict(:input => mx.zeros(input)))
   grads = mxgrads(args)
-  model = @mxerr stacks MXModel(model, params, grads, stacks,
+  model = @mxerr stacks Model(model, params, grads, stacks,
                                 mx.bind(node, args = args,
                                               args_grad = grads,
                                               grad_req = mx.GRAD_ADD))
@@ -44,19 +44,19 @@ function mxnet(model::Model, input)
   return model
 end
 
-function (model::MXModel)(input)
+function runmodel(model::Model, input)
   copy!(model.exec.arg_dict[:input], input)
   mx.forward(model.exec, is_train = true)
   copy(model.exec.outputs[1])
 end
 
-function Flux.back!(model::MXModel, Δ, x)
+function Flux.back!(model::Model, Δ, x)
   ndzero!(model.grads[:input])
   mx.backward(model.exec, tond(Δ))
   copy(model.grads[:input])
 end
 
-function Flux.update!(model::MXModel, η)
+function Flux.update!(model::Model, η)
   for (arg, grad) in zip(model.exec.arg_arrays, model.exec.grad_arrays)
     mx.@nd_as_jl rw = (arg, grad) begin
       arg .-= grad .* η
@@ -81,7 +81,7 @@ function rewrite_softmax(model, name)
   return Flux.Capacitor(vertex(SoftmaxOutput(name), g[1]))
 end
 
-function mx.FeedForward(model::Model; input = :data, label = :softmax, context = mx.cpu())
+function mx.FeedForward(model::Flux.Model; input = :data, label = :softmax, context = mx.cpu())
   model = rewrite_softmax(model, label)
   node, vars = mxgraph(model, input)
   ff = mx.FeedForward(node, context = context)