diff --git a/src/NNlib.jl b/src/NNlib.jl
index c6212554e..da0d24025 100644
--- a/src/NNlib.jl
+++ b/src/NNlib.jl
@@ -2,7 +2,7 @@ module NNlib
 
 using Requires, Libdl
 
-export σ, sigmoid, relu, leakyrelu, elu, swish, selu, softplus, softsign, logσ, logsigmoid,
+export σ, sigmoid, relu, leakyrelu, elu, gelu, swish, selu, softplus, softsign, logσ, logsigmoid,
   softmax, logsoftmax, maxpool, meanpool
 
 include("numeric.jl")
diff --git a/src/activation.jl b/src/activation.jl
index 9f45b25d4..b5cc8017d 100644
--- a/src/activation.jl
+++ b/src/activation.jl
@@ -66,6 +66,20 @@ You can also specify the coefficient explicitly, e.g. `elu(x, 1)`.
 """
 elu(x, α = one(x)) = ifelse(x ≥ 0, x/1, α * (exp(x) - one(x)))
 
+"""
+    gelu(x) = 0.5x*(1 + tanh(√(2/π)*(x + 0.044715x^3)))
+
+[Gaussian Error Linear Unit](https://arxiv.org/pdf/1606.08415.pdf)
+activation function.
+"""
+function gelu(x)
+    λ = oftype(x/1, √(2/π))
+    α = oftype(x/1, 0.044715)
+    h = oftype(x/1, 0.5)
+    h * x * (one(x) + tanh(λ * (x + α * x^3)))
+end
+
+
 """
     swish(x) = x * σ(x)
 
diff --git a/test/activation.jl b/test/activation.jl
index d3400a257..9222721e7 100644
--- a/test/activation.jl
+++ b/test/activation.jl
@@ -1,4 +1,4 @@
-ACTIVATION_FUNCTIONS = [σ, relu, leakyrelu, elu, swish, selu, softplus, softsign];
+ACTIVATION_FUNCTIONS = [σ, relu, leakyrelu, elu, gelu, swish, selu, softplus, softsign];
 
 function test_value_float_precision_preserving(a)
     @testset "$(a): " begin
@@ -42,6 +42,7 @@ end
   @test relu(0.0) == 0.0
   @test leakyrelu(0.0) == 0.0
   @test elu(0.0) == 0.0
+  @test gelu(0.0) == 0.0
   @test swish(0.0) == 0.0
   @test softplus(0.0) ≈ log(2.0)
   @test softsign(0.0) == 0.0
@@ -51,6 +52,7 @@ end
   @test relu(1.0) == 1.0
   @test leakyrelu(1.0) == 1.0
   @test elu(1.0) == 1.0
+  @test gelu(1.0) == 0.8411919906082768
   @test swish(1.0) == 1.0 / (1.0 + exp(-1.0))
   @test softplus(1.0) ≈ log(exp(1.0) + 1.0)
   @test softsign(1.0) == 0.5
@@ -60,6 +62,7 @@ end
   @test relu(-1.0) == 0.0
   @test leakyrelu(-1.0) == -0.01
   @test elu(-1.0) == exp(-1.0) - 1.0
+  @test gelu(-1.0) == -0.15880800939172324
   @test swish(-1.0) == -1.0 / (1.0 + exp(1.0))
   @test softplus(-1.0) ≈ log(exp(-1.0) + 1.0)
   @test softsign(-1.0) == -0.5