diff --git a/src/cnn.c b/src/cnn.c
index 24b2b110..188cf14e 100644
--- a/src/cnn.c
+++ b/src/cnn.c
@@ -355,6 +355,16 @@ void train_cifar10()
     free_data(train);
 }
 
+void compare_nist(char *p1,char *p2)
+{
+    srand(222222);
+    network n1 = parse_network_cfg(p1);
+    network n2 = parse_network_cfg(p2);
+    data test = load_categorical_data_csv("data/mnist/mnist_test.csv",0,10);
+    normalize_data_rows(test);
+    compare_networks(n1, n2, test);
+}
+
 void test_nist(char *path)
 {
     srand(222222);
@@ -377,7 +387,7 @@ void train_nist(char *cfgfile)
     normalize_data_rows(test);
     int count = 0;
     int iters = 60000/net.batch + 1;
-    while(++count <= 200){
+    while(++count <= 10){
         clock_t start = clock(), end;
         float loss = train_network_sgd(net, train, iters);
         end = clock();
@@ -625,6 +635,11 @@ int main(int argc, char **argv)
     else if(0==strcmp(argv[1], "visualize")) test_visualize(argv[2]);
     else if(0==strcmp(argv[1], "valid")) validate_imagenet(argv[2]);
     else if(0==strcmp(argv[1], "testnist")) test_nist(argv[2]);
+    else if(argc < 4){
+        fprintf(stderr, "usage: %s <function> <filename> <filename>\n", argv[0]);
+        return 0;
+    }
+    else if(0==strcmp(argv[1], "compare")) compare_nist(argv[2], argv[3]);
     fprintf(stderr, "Success!\n");
     return 0;
 }
diff --git a/src/network.c b/src/network.c
index 829bb6ed..ac166a6f 100644
--- a/src/network.c
+++ b/src/network.c
@@ -645,6 +645,28 @@ void print_network(network net)
     }
 }
 
+void compare_networks(network n1, network n2, data test)
+{
+    matrix g1 = network_predict_data(n1, test);
+    matrix g2 = network_predict_data(n2, test);
+    int i;
+    int a,b,c,d;
+    a = b = c = d = 0;
+    for(i = 0; i < g1.rows; ++i){
+        int truth = max_index(test.y.vals[i], test.y.cols);
+        int p1 = max_index(g1.vals[i], g1.cols);
+        int p2 = max_index(g2.vals[i], g2.cols);
+        if(p1 == truth){
+            if(p2 == truth) ++d;
+            else ++c;
+        }else{
+            if(p2 == truth) ++b;
+            else ++a;
+        }
+    }
+    printf("%5d %5d\n%5d %5d\n", a, b, c, d);
+}
+
 float network_accuracy(network net, data d)
 {
     matrix guess = network_predict_data(net, d);
diff --git a/src/network.h b/src/network.h
index 6eb75451..7a401bdf 100644
--- a/src/network.h
+++ b/src/network.h
@@ -40,6 +40,8 @@ float train_network_datum_gpu(network net, float *x, float *y);
 float *network_predict_gpu(network net, float *input);
 #endif
 
+void compare_networks(network n1, network n2, data d);
+
 network make_network(int n, int batch);
 void forward_network(network net, float *input, float *truth, int train);
 void backward_network(network net, float *input);
diff --git a/src/utils.c b/src/utils.c
index 365faebc..682d3043 100644
--- a/src/utils.c
+++ b/src/utils.c
@@ -243,6 +243,7 @@ void scale_array(float *a, int n, float s)
         a[i] *= s;
     }
 }
+
 int max_index(float *a, int n)
 {
     if(n <= 0) return -1;